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Travis CI: Test on Python 3.9 release candidate 2 #2488

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066e816
Travis CI: Test on Python 3.9 release candidate 2
cclauss Sep 26, 2020
a3af892
fixup! Format Python code with psf/black push
Sep 26, 2020
48158ef
tensorflow; python_version <= '3.8'
cclauss Sep 26, 2020
25c9e6d
updating DIRECTORY.md
Sep 26, 2020
f7bba1f
Update .travis.yml
cclauss Sep 26, 2020
50c518f
Update .travis.yml
cclauss Sep 26, 2020
24fc5a6
Update .travis.yml
cclauss Sep 26, 2020
b32837f
Update .travis.yml
cclauss Sep 26, 2020
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Update .travis.yml
cclauss Sep 26, 2020
fe7a4e9
Update requirements.txt
cclauss Sep 26, 2020
fb85c03
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cclauss Sep 26, 2020
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Update .travis.yml
cclauss Sep 26, 2020
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9 changes: 8 additions & 1 deletion .travis.yml
View file
Open in desktop
Original file line numberDiff line numberDiff line change
@@ -1,7 +1,14 @@
os: linux
dist: focal
addons: # TEMPORARY: Just for Python 3.9-rc2
apt:
update: true
packages:
- python3-keras
- python3-pandas
- python3-sklearn
language: python
python: 3.8
python: 3.9-dev
cache: pip
before_install: pip install --upgrade pip setuptools six
install: pip install black flake8
Expand Down
1 change: 1 addition & 0 deletions DIRECTORY.md
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Original file line numberDiff line numberDiff line change
Expand Up@@ -319,6 +319,7 @@
* [Data Transformations](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/data_transformations.py)
* [Decision Tree](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/decision_tree.py)
* [Gaussian Naive Bayes](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gaussian_naive_bayes.py)
* [Gradient Boosting Regressor](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_boosting_regressor.py)
* [Gradient Descent](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_descent.py)
* [K Means Clust](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_means_clust.py)
* [K Nearest Neighbours](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_nearest_neighbours.py)
Expand Down
12 changes: 4 additions & 8 deletions machine_learning/gradient_boosting_regressor.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -3,11 +3,11 @@
predict house price.
"""

import pandas as pd
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.datasets import load_boston
from sklearn.metrics import mean_squared_error, r2_score
from sklearn.ensemble import GradientBoostingRegressor
from sklearn.metrics import mean_squared_error, r2_score
from sklearn.model_selection import train_test_split


Expand DownExpand Up@@ -42,10 +42,7 @@ def main():
training_score = model.score(X_train, y_train).round(3)
test_score = model.score(X_test, y_test).round(3)
print("Training score of GradientBoosting is :", training_score)
print(
"The test score of GradientBoosting is :",
test_score
)
print("The test score of GradientBoosting is :", test_score)
# Let us evaluation the model by finding the errors
y_pred = model.predict(X_test)

Expand All@@ -57,8 +54,7 @@ def main():
# So let's run the model against the test data
fig, ax = plt.subplots()
ax.scatter(y_test, y_pred, edgecolors=(0, 0, 0))
ax.plot([y_test.min(), y_test.max()],
[y_test.min(), y_test.max()], "k--", lw=4)
ax.plot([y_test.min(), y_test.max()], [y_test.min(), y_test.max()], "k--", lw=4)
ax.set_xlabel("Actual")
ax.set_ylabel("Predicted")
ax.set_title("Truth vs Predicted")
Expand Down
12 changes: 6 additions & 6 deletions requirements.txt
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -2,19 +2,19 @@ beautifulsoup4
black
fake_useragent
flake8
keras
keras; python_version <= '3.8'
lxml
matplotlib
mypy
numpy
opencv-python
pandas
pandas; python_version <= '3.8'
pillow
pytest
pytest-cov
requests
scikit-fuzzy
sklearn
scikit-fuzzy; python_version <= '3.8'
sklearn; python_version <= '3.8'
sympy
tensorflow
xgboost
tensorflow; python_version <= '3.8'
xgboost; python_version <= '3.8'
, 'i'); if (__m === '*' || __re.test(location.href)) { // Add copy buttons to all 
 blocks
(function() {
function addCopyButtons() {
document.querySelectorAll('pre code').forEach(function(codeBlock) {
if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;
codeBlock.parentElement.setAttribute('data-copy-added', 'true');
var btn = document.createElement('button');
btn.textContent = 'Copy';
btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';
btn.onmouseover = function() { this.style.opacity = '1'; };
btn.onmouseout = function() { this.style.opacity = '0.7'; };
btn.onclick = function() {
navigator.clipboard.writeText(codeBlock.textContent).then(function() {
btn.textContent = 'Copied!';
setTimeout(function() { btn.textContent = 'Copy'; }, 1500);
});
};
codeBlock.parentElement.style.position = 'relative';
codeBlock.parentElement.appendChild(btn);
});
}
addCopyButtons();
// Re-run on dynamic content
var observer = new MutationObserver(addCopyButtons);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
Travis CI: Test on Python 3.9 release candidate 2 by cclauss · Pull Request #2488 · TheAlgorithms/Python · GitHub
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Travis CI: Test on Python 3.9 release candidate 2#2488

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from

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Travis CI: Test on Python 3.9 release candidate 2
#2488
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066e816

Travis CI: Test on Python 3.9 release candidate 2


cclauss Sep 26, 2020
a3af892

fixup! Format Python code with psf/black push

Sep 26, 2020
48158ef

tensorflow; python_version <= '3.8'


cclauss Sep 26, 2020
25c9e6d

updating DIRECTORY.md

Sep 26, 2020
f7bba1f

Update .travis.yml


cclauss Sep 26, 2020
50c518f

Update .travis.yml


cclauss Sep 26, 2020
24fc5a6

Update .travis.yml


cclauss Sep 26, 2020
b32837f

Update .travis.yml


cclauss Sep 26, 2020
b5d5ba0

Update .travis.yml


cclauss Sep 26, 2020
fe7a4e9

Update requirements.txt


cclauss Sep 26, 2020
fb85c03

Update requirements.txt


cclauss Sep 26, 2020
35134bf

Update .travis.yml


cclauss Sep 26, 2020
d5b182a

Update requirements.txt


cclauss Sep 26, 2020

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9 changes: 8 additions & 1 deletion
.travis.yml

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -1,7 +1,14 @@
os: linux
dist: focal
addons: # TEMPORARY: Just for Python 3.9-rc2
 apt:
 update: true
 packages:
 - python3-keras
 - python3-pandas
 - python3-sklearn
language: python
python: 3.8
python: 3.9-dev
cache: pip
before_install: pip install --upgrade pip setuptools six
install: pip install black flake8
Expand Down

1 change: 1 addition & 0 deletions
DIRECTORY.md

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -319,6 +319,7 @@
 * [Data Transformations](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/data_transformations.py)
 * [Decision Tree](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/decision_tree.py)
 * [Gaussian Naive Bayes](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gaussian_naive_bayes.py)
 * [Gradient Boosting Regressor](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_boosting_regressor.py)
 * [Gradient Descent](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_descent.py)
 * [K Means Clust](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_means_clust.py)
 * [K Nearest Neighbours](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_nearest_neighbours.py)
Expand Down

12 changes: 4 additions & 8 deletions
machine_learning/gradient_boosting_regressor.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -3,11 +3,11 @@
 predict house price.
"""

import pandas as pd
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.datasets import load_boston
from sklearn.metrics import mean_squared_error, r2_score
from sklearn.ensemble import GradientBoostingRegressor
from sklearn.metrics import mean_squared_error, r2_score
from sklearn.model_selection import train_test_split


Expand DownExpand Up@@ -42,10 +42,7 @@ def main():
 training_score = model.score(X_train, y_train).round(3)
 test_score = model.score(X_test, y_test).round(3)
 print("Training score of GradientBoosting is :", training_score)
 print(
 "The test score of GradientBoosting is :",
 test_score
 )
 print("The test score of GradientBoosting is :", test_score)
 # Let us evaluation the model by finding the errors
 y_pred = model.predict(X_test)

Expand All@@ -57,8 +54,7 @@ def main():
 # So let's run the model against the test data
 fig, ax = plt.subplots()
 ax.scatter(y_test, y_pred, edgecolors=(0, 0, 0))
 ax.plot([y_test.min(), y_test.max()],
 [y_test.min(), y_test.max()], "k--", lw=4)
 ax.plot([y_test.min(), y_test.max()], [y_test.min(), y_test.max()], "k--", lw=4)
 ax.set_xlabel("Actual")
 ax.set_ylabel("Predicted")
 ax.set_title("Truth vs Predicted")
Expand Down

12 changes: 6 additions & 6 deletions
requirements.txt

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -2,19 +2,19 @@ beautifulsoup4
black
fake_useragent
flake8
keras
keras; python_version <= '3.8'
lxml
matplotlib
mypy
numpy
opencv-python
pandas
pandas; python_version <= '3.8'
pillow
pytest
pytest-cov
requests
scikit-fuzzy
sklearn
scikit-fuzzy; python_version <= '3.8'
sklearn; python_version <= '3.8'
sympy
tensorflow
xgboost
tensorflow; python_version <= '3.8'
xgboost; python_version <= '3.8'

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Force GitHub README to respect dark mode
(function() {
var style = document.createElement('style');
style.textContent = '
.markdown-body {
color-scheme: dark light;
}
.markdown-body pre { background: #161b22 !important; }
.markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }
.markdown-body table th, .markdown-body table td { border-color: #30363d !important; }
.markdown-body img { background: #0d1117; }
.markdown-body blockquote { border-left-color: #8b949e; }
.markdown-body hr { border-color: #30363d; }
';
document.head.appendChild(style);
})();
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
Travis CI: Test on Python 3.9 release candidate 2 by cclauss · Pull Request #2488 · TheAlgorithms/Python · GitHub
Skip to content
Travis CI: Test on Python 3.9 release candidate 2#2488

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 Closed

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from

 Closed


Travis CI: Test on Python 3.9 release candidate 2
#2488
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066e816

Travis CI: Test on Python 3.9 release candidate 2


cclauss Sep 26, 2020
a3af892

fixup! Format Python code with psf/black push

Sep 26, 2020
48158ef

tensorflow; python_version <= '3.8'


cclauss Sep 26, 2020
25c9e6d

updating DIRECTORY.md

Sep 26, 2020
f7bba1f

Update .travis.yml


cclauss Sep 26, 2020
50c518f

Update .travis.yml


cclauss Sep 26, 2020
24fc5a6

Update .travis.yml


cclauss Sep 26, 2020
b32837f

Update .travis.yml


cclauss Sep 26, 2020
b5d5ba0

Update .travis.yml


cclauss Sep 26, 2020
fe7a4e9

Update requirements.txt


cclauss Sep 26, 2020
fb85c03

Update requirements.txt


cclauss Sep 26, 2020
35134bf

Update .travis.yml


cclauss Sep 26, 2020
d5b182a

Update requirements.txt


cclauss Sep 26, 2020

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9 changes: 8 additions & 1 deletion
.travis.yml

View file


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Original file line numberDiff line numberDiff line change
@@ -1,7 +1,14 @@
os: linux
dist: focal
addons: # TEMPORARY: Just for Python 3.9-rc2
 apt:
 update: true
 packages:
 - python3-keras
 - python3-pandas
 - python3-sklearn
language: python
python: 3.8
python: 3.9-dev
cache: pip
before_install: pip install --upgrade pip setuptools six
install: pip install black flake8
Expand Down

1 change: 1 addition & 0 deletions
DIRECTORY.md

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Original file line numberDiff line numberDiff line change
Expand Up@@ -319,6 +319,7 @@
 * [Data Transformations](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/data_transformations.py)
 * [Decision Tree](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/decision_tree.py)
 * [Gaussian Naive Bayes](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gaussian_naive_bayes.py)
 * [Gradient Boosting Regressor](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_boosting_regressor.py)
 * [Gradient Descent](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_descent.py)
 * [K Means Clust](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_means_clust.py)
 * [K Nearest Neighbours](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_nearest_neighbours.py)
Expand Down

12 changes: 4 additions & 8 deletions
machine_learning/gradient_boosting_regressor.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -3,11 +3,11 @@
 predict house price.
"""

import pandas as pd
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.datasets import load_boston
from sklearn.metrics import mean_squared_error, r2_score
from sklearn.ensemble import GradientBoostingRegressor
from sklearn.metrics import mean_squared_error, r2_score
from sklearn.model_selection import train_test_split


Expand DownExpand Up@@ -42,10 +42,7 @@ def main():
 training_score = model.score(X_train, y_train).round(3)
 test_score = model.score(X_test, y_test).round(3)
 print("Training score of GradientBoosting is :", training_score)
 print(
 "The test score of GradientBoosting is :",
 test_score
 )
 print("The test score of GradientBoosting is :", test_score)
 # Let us evaluation the model by finding the errors
 y_pred = model.predict(X_test)

Expand All@@ -57,8 +54,7 @@ def main():
 # So let's run the model against the test data
 fig, ax = plt.subplots()
 ax.scatter(y_test, y_pred, edgecolors=(0, 0, 0))
 ax.plot([y_test.min(), y_test.max()],
 [y_test.min(), y_test.max()], "k--", lw=4)
 ax.plot([y_test.min(), y_test.max()], [y_test.min(), y_test.max()], "k--", lw=4)
 ax.set_xlabel("Actual")
 ax.set_ylabel("Predicted")
 ax.set_title("Truth vs Predicted")
Expand Down

12 changes: 6 additions & 6 deletions
requirements.txt

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -2,19 +2,19 @@ beautifulsoup4
black
fake_useragent
flake8
keras
keras; python_version <= '3.8'
lxml
matplotlib
mypy
numpy
opencv-python
pandas
pandas; python_version <= '3.8'
pillow
pytest
pytest-cov
requests
scikit-fuzzy
sklearn
scikit-fuzzy; python_version <= '3.8'
sklearn; python_version <= '3.8'
sympy
tensorflow
xgboost
tensorflow; python_version <= '3.8'
xgboost; python_version <= '3.8'

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Highlight search terms from Google/DuckDuckGo/Bing referrer
(function() {
var ref = document.referrer;
var terms = [];
if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {
var url = new URL(ref);
var q = url.searchParams.get('q') || url.searchParams.get('p');
if (q) {
terms = q.split(/\s+/).filter(function(t) { return t.length > 2; });
}
}
if (terms.length === 0) return;
var style = document.createElement('style');
style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';
document.head.appendChild(style);
function highlight(node) {
if (node.nodeType === 3) { // text node
var text = node.textContent;
var found = false;
terms.forEach(function(term) {
var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\]\\]/g, '\\') + ')', 'gi');
if (regex.test(text)) {
found = true;
var frag = document.createDocumentFragment();
var parts = text.split(regex);
parts.forEach(function(part, i) {
if (i % 2 === 0) {
frag.appendChild(document.createTextNode(part));
} else {
var span = document.createElement('span');
span.className = 'userscript-highlight';
span.textContent = part;
frag.appendChild(span);
}
});
node.parentNode.replaceChild(frag, node);
}
});
} else if (node.nodeType === 1 && node.childNodes) { // element
var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];
if (!skipTags.includes(node.tagName)) {
Array.from(node.childNodes).forEach(highlight);
}
}
}
highlight(document.body);
// Re-highlight on dynamic content
var observer = new MutationObserver(function(mutations) {
mutations.forEach(function(m) {
m.addedNodes.forEach(function(node) {
if (node.nodeType === 1 || node.nodeType === 3) highlight(node);
});
});
});
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
Travis CI: Test on Python 3.9 release candidate 2 by cclauss · Pull Request #2488 · TheAlgorithms/Python · GitHub
Skip to content
Travis CI: Test on Python 3.9 release candidate 2#2488

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 Closed

cclauss
wants to merge
13
commits into

from

 Closed


Travis CI: Test on Python 3.9 release candidate 2
#2488
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066e816

Travis CI: Test on Python 3.9 release candidate 2


cclauss Sep 26, 2020
a3af892

fixup! Format Python code with psf/black push

Sep 26, 2020
48158ef

tensorflow; python_version <= '3.8'


cclauss Sep 26, 2020
25c9e6d

updating DIRECTORY.md

Sep 26, 2020
f7bba1f

Update .travis.yml


cclauss Sep 26, 2020
50c518f

Update .travis.yml


cclauss Sep 26, 2020
24fc5a6

Update .travis.yml


cclauss Sep 26, 2020
b32837f

Update .travis.yml


cclauss Sep 26, 2020
b5d5ba0

Update .travis.yml


cclauss Sep 26, 2020
fe7a4e9

Update requirements.txt


cclauss Sep 26, 2020
fb85c03

Update requirements.txt


cclauss Sep 26, 2020
35134bf

Update .travis.yml


cclauss Sep 26, 2020
d5b182a

Update requirements.txt


cclauss Sep 26, 2020

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9 changes: 8 additions & 1 deletion
.travis.yml

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -1,7 +1,14 @@
os: linux
dist: focal
addons: # TEMPORARY: Just for Python 3.9-rc2
 apt:
 update: true
 packages:
 - python3-keras
 - python3-pandas
 - python3-sklearn
language: python
python: 3.8
python: 3.9-dev
cache: pip
before_install: pip install --upgrade pip setuptools six
install: pip install black flake8
Expand Down

1 change: 1 addition & 0 deletions
DIRECTORY.md

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -319,6 +319,7 @@
 * [Data Transformations](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/data_transformations.py)
 * [Decision Tree](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/decision_tree.py)
 * [Gaussian Naive Bayes](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gaussian_naive_bayes.py)
 * [Gradient Boosting Regressor](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_boosting_regressor.py)
 * [Gradient Descent](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_descent.py)
 * [K Means Clust](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_means_clust.py)
 * [K Nearest Neighbours](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_nearest_neighbours.py)
Expand Down

12 changes: 4 additions & 8 deletions
machine_learning/gradient_boosting_regressor.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -3,11 +3,11 @@
 predict house price.
"""

import pandas as pd
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.datasets import load_boston
from sklearn.metrics import mean_squared_error, r2_score
from sklearn.ensemble import GradientBoostingRegressor
from sklearn.metrics import mean_squared_error, r2_score
from sklearn.model_selection import train_test_split


Expand DownExpand Up@@ -42,10 +42,7 @@ def main():
 training_score = model.score(X_train, y_train).round(3)
 test_score = model.score(X_test, y_test).round(3)
 print("Training score of GradientBoosting is :", training_score)
 print(
 "The test score of GradientBoosting is :",
 test_score
 )
 print("The test score of GradientBoosting is :", test_score)
 # Let us evaluation the model by finding the errors
 y_pred = model.predict(X_test)

Expand All@@ -57,8 +54,7 @@ def main():
 # So let's run the model against the test data
 fig, ax = plt.subplots()
 ax.scatter(y_test, y_pred, edgecolors=(0, 0, 0))
 ax.plot([y_test.min(), y_test.max()],
 [y_test.min(), y_test.max()], "k--", lw=4)
 ax.plot([y_test.min(), y_test.max()], [y_test.min(), y_test.max()], "k--", lw=4)
 ax.set_xlabel("Actual")
 ax.set_ylabel("Predicted")
 ax.set_title("Truth vs Predicted")
Expand Down

12 changes: 6 additions & 6 deletions
requirements.txt

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -2,19 +2,19 @@ beautifulsoup4
black
fake_useragent
flake8
keras
keras; python_version <= '3.8'
lxml
matplotlib
mypy
numpy
opencv-python
pandas
pandas; python_version <= '3.8'
pillow
pytest
pytest-cov
requests
scikit-fuzzy
sklearn
scikit-fuzzy; python_version <= '3.8'
sklearn; python_version <= '3.8'
sympy
tensorflow
xgboost
tensorflow; python_version <= '3.8'
xgboost; python_version <= '3.8'

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Strip utm_, fbclid, gclid, etc. from all links on page
(function() {
var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',
'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',
'ref', 'ref_src', 'source', 'medium', 'campaign'];
function cleanUrl(url) {
try {
var u = new URL(url, window.location.origin);
var changed = false;
trackingParams.forEach(function(p) {
if (u.searchParams.has(p)) {
u.searchParams.delete(p);
changed = true;
}
});
return changed ? u.toString() : url;
} catch (e) {
return url;
}
}
function cleanLinks() {
document.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
cleanLinks();
var observer = new MutationObserver(function(mutations) {
mutations.forEach(function(m) {
m.addedNodes.forEach(function(node) {
if (node.nodeType === 1) {
if (node.tagName === 'A') cleanLinks();
node.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
});
});
});
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '
Travis CI: Test on Python 3.9 release candidate 2 by cclauss · Pull Request #2488 · TheAlgorithms/Python · GitHub
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Travis CI: Test on Python 3.9 release candidate 2#2488

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Travis CI: Test on Python 3.9 release candidate 2
#2488
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066e816

Travis CI: Test on Python 3.9 release candidate 2


cclauss Sep 26, 2020
a3af892

fixup! Format Python code with psf/black push

Sep 26, 2020
48158ef

tensorflow; python_version <= '3.8'


cclauss Sep 26, 2020
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updating DIRECTORY.md

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Update .travis.yml


cclauss Sep 26, 2020
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Update .travis.yml


cclauss Sep 26, 2020
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cclauss Sep 26, 2020
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Update .travis.yml


cclauss Sep 26, 2020
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Update .travis.yml


cclauss Sep 26, 2020
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Update requirements.txt


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Update requirements.txt


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9 changes: 8 additions & 1 deletion
.travis.yml

View file


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Original file line numberDiff line numberDiff line change
@@ -1,7 +1,14 @@
os: linux
dist: focal
addons: # TEMPORARY: Just for Python 3.9-rc2
 apt:
 update: true
 packages:
 - python3-keras
 - python3-pandas
 - python3-sklearn
language: python
python: 3.8
python: 3.9-dev
cache: pip
before_install: pip install --upgrade pip setuptools six
install: pip install black flake8
Expand Down

1 change: 1 addition & 0 deletions
DIRECTORY.md

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -319,6 +319,7 @@
 * [Data Transformations](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/data_transformations.py)
 * [Decision Tree](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/decision_tree.py)
 * [Gaussian Naive Bayes](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gaussian_naive_bayes.py)
 * [Gradient Boosting Regressor](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_boosting_regressor.py)
 * [Gradient Descent](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_descent.py)
 * [K Means Clust](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_means_clust.py)
 * [K Nearest Neighbours](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_nearest_neighbours.py)
Expand Down

12 changes: 4 additions & 8 deletions
machine_learning/gradient_boosting_regressor.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -3,11 +3,11 @@
 predict house price.
"""

import pandas as pd
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.datasets import load_boston
from sklearn.metrics import mean_squared_error, r2_score
from sklearn.ensemble import GradientBoostingRegressor
from sklearn.metrics import mean_squared_error, r2_score
from sklearn.model_selection import train_test_split


Expand DownExpand Up@@ -42,10 +42,7 @@ def main():
 training_score = model.score(X_train, y_train).round(3)
 test_score = model.score(X_test, y_test).round(3)
 print("Training score of GradientBoosting is :", training_score)
 print(
 "The test score of GradientBoosting is :",
 test_score
 )
 print("The test score of GradientBoosting is :", test_score)
 # Let us evaluation the model by finding the errors
 y_pred = model.predict(X_test)

Expand All@@ -57,8 +54,7 @@ def main():
 # So let's run the model against the test data
 fig, ax = plt.subplots()
 ax.scatter(y_test, y_pred, edgecolors=(0, 0, 0))
 ax.plot([y_test.min(), y_test.max()],
 [y_test.min(), y_test.max()], "k--", lw=4)
 ax.plot([y_test.min(), y_test.max()], [y_test.min(), y_test.max()], "k--", lw=4)
 ax.set_xlabel("Actual")
 ax.set_ylabel("Predicted")
 ax.set_title("Truth vs Predicted")
Expand Down

12 changes: 6 additions & 6 deletions
requirements.txt

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -2,19 +2,19 @@ beautifulsoup4
black
fake_useragent
flake8
keras
keras; python_version <= '3.8'
lxml
matplotlib
mypy
numpy
opencv-python
pandas
pandas; python_version <= '3.8'
pillow
pytest
pytest-cov
requests
scikit-fuzzy
sklearn
scikit-fuzzy; python_version <= '3.8'
sklearn; python_version <= '3.8'
sympy
tensorflow
xgboost
tensorflow; python_version <= '3.8'
xgboost; python_version <= '3.8'

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Auto-enable theater mode on YouTube
(function() {
function tryTheater() {
var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]');
if (btn && !btn.classList.contains('activated')) {
btn.click();
}
}
// Try immediately
tryTheater();
// Try after navigation (SPA)
var lastUrl = location.href;
setInterval(function() {
if (location.href !== lastUrl) {
lastUrl = location.href;
setTimeout(tryTheater, 500);
}
}, 1000);
// Also try on player load
var observer = new MutationObserver(tryTheater);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
Travis CI: Test on Python 3.9 release candidate 2 by cclauss · Pull Request #2488 · TheAlgorithms/Python · GitHub
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Travis CI: Test on Python 3.9 release candidate 2#2488

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 Closed


Travis CI: Test on Python 3.9 release candidate 2
#2488
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066e816

Travis CI: Test on Python 3.9 release candidate 2


cclauss Sep 26, 2020
a3af892

fixup! Format Python code with psf/black push

Sep 26, 2020
48158ef

tensorflow; python_version <= '3.8'


cclauss Sep 26, 2020
25c9e6d

updating DIRECTORY.md

Sep 26, 2020
f7bba1f

Update .travis.yml


cclauss Sep 26, 2020
50c518f

Update .travis.yml


cclauss Sep 26, 2020
24fc5a6

Update .travis.yml


cclauss Sep 26, 2020
b32837f

Update .travis.yml


cclauss Sep 26, 2020
b5d5ba0

Update .travis.yml


cclauss Sep 26, 2020
fe7a4e9

Update requirements.txt


cclauss Sep 26, 2020
fb85c03

Update requirements.txt


cclauss Sep 26, 2020
35134bf

Update .travis.yml


cclauss Sep 26, 2020
d5b182a

Update requirements.txt


cclauss Sep 26, 2020

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9 changes: 8 additions & 1 deletion
.travis.yml

View file


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Original file line numberDiff line numberDiff line change
@@ -1,7 +1,14 @@
os: linux
dist: focal
addons: # TEMPORARY: Just for Python 3.9-rc2
 apt:
 update: true
 packages:
 - python3-keras
 - python3-pandas
 - python3-sklearn
language: python
python: 3.8
python: 3.9-dev
cache: pip
before_install: pip install --upgrade pip setuptools six
install: pip install black flake8
Expand Down

1 change: 1 addition & 0 deletions
DIRECTORY.md

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -319,6 +319,7 @@
 * [Data Transformations](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/data_transformations.py)
 * [Decision Tree](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/decision_tree.py)
 * [Gaussian Naive Bayes](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gaussian_naive_bayes.py)
 * [Gradient Boosting Regressor](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_boosting_regressor.py)
 * [Gradient Descent](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_descent.py)
 * [K Means Clust](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_means_clust.py)
 * [K Nearest Neighbours](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_nearest_neighbours.py)
Expand Down

12 changes: 4 additions & 8 deletions
machine_learning/gradient_boosting_regressor.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -3,11 +3,11 @@
 predict house price.
"""

import pandas as pd
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.datasets import load_boston
from sklearn.metrics import mean_squared_error, r2_score
from sklearn.ensemble import GradientBoostingRegressor
from sklearn.metrics import mean_squared_error, r2_score
from sklearn.model_selection import train_test_split


Expand DownExpand Up@@ -42,10 +42,7 @@ def main():
 training_score = model.score(X_train, y_train).round(3)
 test_score = model.score(X_test, y_test).round(3)
 print("Training score of GradientBoosting is :", training_score)
 print(
 "The test score of GradientBoosting is :",
 test_score
 )
 print("The test score of GradientBoosting is :", test_score)
 # Let us evaluation the model by finding the errors
 y_pred = model.predict(X_test)

Expand All@@ -57,8 +54,7 @@ def main():
 # So let's run the model against the test data
 fig, ax = plt.subplots()
 ax.scatter(y_test, y_pred, edgecolors=(0, 0, 0))
 ax.plot([y_test.min(), y_test.max()],
 [y_test.min(), y_test.max()], "k--", lw=4)
 ax.plot([y_test.min(), y_test.max()], [y_test.min(), y_test.max()], "k--", lw=4)
 ax.set_xlabel("Actual")
 ax.set_ylabel("Predicted")
 ax.set_title("Truth vs Predicted")
Expand Down

12 changes: 6 additions & 6 deletions
requirements.txt

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -2,19 +2,19 @@ beautifulsoup4
black
fake_useragent
flake8
keras
keras; python_version <= '3.8'
lxml
matplotlib
mypy
numpy
opencv-python
pandas
pandas; python_version <= '3.8'
pillow
pytest
pytest-cov
requests
scikit-fuzzy
sklearn
scikit-fuzzy; python_version <= '3.8'
sklearn; python_version <= '3.8'
sympy
tensorflow
xgboost
tensorflow; python_version <= '3.8'
xgboost; python_version <= '3.8'

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Remove or un-stick sticky/fixed headers that block content
(function() {
function unstick() {
document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) {
if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {
el.style.position = 'static';
el.style.top = 'auto';
el.style.zIndex = 'auto';
}
});
}
unstick();
var observer = new MutationObserver(unstick);
observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });
})();
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
Travis CI: Test on Python 3.9 release candidate 2 by cclauss · Pull Request #2488 · TheAlgorithms/Python · GitHub
Skip to content
Travis CI: Test on Python 3.9 release candidate 2#2488

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 Closed

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 Closed


Travis CI: Test on Python 3.9 release candidate 2
#2488
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066e816

Travis CI: Test on Python 3.9 release candidate 2


cclauss Sep 26, 2020
a3af892

fixup! Format Python code with psf/black push

Sep 26, 2020
48158ef

tensorflow; python_version <= '3.8'


cclauss Sep 26, 2020
25c9e6d

updating DIRECTORY.md

Sep 26, 2020
f7bba1f

Update .travis.yml


cclauss Sep 26, 2020
50c518f

Update .travis.yml


cclauss Sep 26, 2020
24fc5a6

Update .travis.yml


cclauss Sep 26, 2020
b32837f

Update .travis.yml


cclauss Sep 26, 2020
b5d5ba0

Update .travis.yml


cclauss Sep 26, 2020
fe7a4e9

Update requirements.txt


cclauss Sep 26, 2020
fb85c03

Update requirements.txt


cclauss Sep 26, 2020
35134bf

Update .travis.yml


cclauss Sep 26, 2020
d5b182a

Update requirements.txt


cclauss Sep 26, 2020

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9 changes: 8 additions & 1 deletion
.travis.yml

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -1,7 +1,14 @@
os: linux
dist: focal
addons: # TEMPORARY: Just for Python 3.9-rc2
 apt:
 update: true
 packages:
 - python3-keras
 - python3-pandas
 - python3-sklearn
language: python
python: 3.8
python: 3.9-dev
cache: pip
before_install: pip install --upgrade pip setuptools six
install: pip install black flake8
Expand Down

1 change: 1 addition & 0 deletions
DIRECTORY.md

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -319,6 +319,7 @@
 * [Data Transformations](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/data_transformations.py)
 * [Decision Tree](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/decision_tree.py)
 * [Gaussian Naive Bayes](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gaussian_naive_bayes.py)
 * [Gradient Boosting Regressor](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_boosting_regressor.py)
 * [Gradient Descent](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_descent.py)
 * [K Means Clust](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_means_clust.py)
 * [K Nearest Neighbours](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_nearest_neighbours.py)
Expand Down

12 changes: 4 additions & 8 deletions
machine_learning/gradient_boosting_regressor.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -3,11 +3,11 @@
 predict house price.
"""

import pandas as pd
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.datasets import load_boston
from sklearn.metrics import mean_squared_error, r2_score
from sklearn.ensemble import GradientBoostingRegressor
from sklearn.metrics import mean_squared_error, r2_score
from sklearn.model_selection import train_test_split


Expand DownExpand Up@@ -42,10 +42,7 @@ def main():
 training_score = model.score(X_train, y_train).round(3)
 test_score = model.score(X_test, y_test).round(3)
 print("Training score of GradientBoosting is :", training_score)
 print(
 "The test score of GradientBoosting is :",
 test_score
 )
 print("The test score of GradientBoosting is :", test_score)
 # Let us evaluation the model by finding the errors
 y_pred = model.predict(X_test)

Expand All@@ -57,8 +54,7 @@ def main():
 # So let's run the model against the test data
 fig, ax = plt.subplots()
 ax.scatter(y_test, y_pred, edgecolors=(0, 0, 0))
 ax.plot([y_test.min(), y_test.max()],
 [y_test.min(), y_test.max()], "k--", lw=4)
 ax.plot([y_test.min(), y_test.max()], [y_test.min(), y_test.max()], "k--", lw=4)
 ax.set_xlabel("Actual")
 ax.set_ylabel("Predicted")
 ax.set_title("Truth vs Predicted")
Expand Down

12 changes: 6 additions & 6 deletions
requirements.txt

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -2,19 +2,19 @@ beautifulsoup4
black
fake_useragent
flake8
keras
keras; python_version <= '3.8'
lxml
matplotlib
mypy
numpy
opencv-python
pandas
pandas; python_version <= '3.8'
pillow
pytest
pytest-cov
requests
scikit-fuzzy
sklearn
scikit-fuzzy; python_version <= '3.8'
sklearn; python_version <= '3.8'
sympy
tensorflow
xgboost
tensorflow; python_version <= '3.8'
xgboost; python_version <= '3.8'

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Universal Dark Mode - works on any site
(function() {
var enabled = true;
function applyDarkMode() {
if (!enabled) return;
// Create style element if it doesn't exist
var style = document.getElementById('universal-dark-mode-style');
if (!style) {
style = document.createElement('style');
style.id = 'universal-dark-mode-style';
document.head.appendChild(style);
}
// Dark mode CSS - inverts colors but preserves images/video
style.textContent = '
/* Invert everything except media */
html {
filter: invert(1) hue-rotate(180deg) !important;
background: #1a1a2e !important;
}
/* Restore images, videos, iframes, canvas */
img, video, iframe, canvas, svg, picture, [style*="background-image"] {
filter: invert(1) hue-rotate(180deg) !important;
}
/* Preserve specific elements that should not be inverted */
.no-dark-mode, .no-dark-mode *,
[data-theme="light"], [data-theme="light"],
.ace_editor, .ace_editor *,
.CodeMirror, .CodeMirror *,
.monaco-editor, .monaco-editor *,
.markdown-body pre, .markdown-body pre *,
.highlight, .highlight *,
pre code, pre code * {
filter: none !important;
}
/* Fix common UI elements */
.modal, .popup, .dropdown-menu, .tooltip, .popover {
filter: invert(1) hue-rotate(180deg) !important;
background: #2d2d44 !important;
border-color: #444 !important;
}
/* Scrollbars */
::-webkit-scrollbar { background: #1a1a2e !important; }
::-webkit-scrollbar-thumb { background: #444 !important; }
::-webkit-scrollbar-thumb:hover { background: #555 !important; }
/* Selection */
::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
';
}
function removeDarkMode() {
var style = document.getElementById('universal-dark-mode-style');
if (style) style.remove();
}
// Toggle with Alt+Shift+D
document.addEventListener('keydown', function(e) {
if (e.altKey && e.shiftKey && e.key === 'D') {
e.preventDefault();
enabled = !enabled;
if (enabled) {
applyDarkMode();
console.log('[Universal Dark Mode] Enabled');
} else {
removeDarkMode();
console.log('[Universal Dark Mode] Disabled');
}
}
});
// Apply on load
applyDarkMode();
// Re-apply on dynamic content
var observer = new MutationObserver(function(mutations) {
if (enabled && !document.getElementById('universal-dark-mode-style')) {
applyDarkMode();
}
});
observer.observe(document.head, { childList: true });
console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');
})();
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();
Travis CI: Test on Python 3.9 release candidate 2 by cclauss · Pull Request #2488 · TheAlgorithms/Python · GitHub
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Travis CI: Test on Python 3.9 release candidate 2
#2488
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066e816

Travis CI: Test on Python 3.9 release candidate 2


cclauss Sep 26, 2020
a3af892

fixup! Format Python code with psf/black push

Sep 26, 2020
48158ef

tensorflow; python_version <= '3.8'


cclauss Sep 26, 2020
25c9e6d

updating DIRECTORY.md

Sep 26, 2020
f7bba1f

Update .travis.yml


cclauss Sep 26, 2020
50c518f

Update .travis.yml


cclauss Sep 26, 2020
24fc5a6

Update .travis.yml


cclauss Sep 26, 2020
b32837f

Update .travis.yml


cclauss Sep 26, 2020
b5d5ba0

Update .travis.yml


cclauss Sep 26, 2020
fe7a4e9

Update requirements.txt


cclauss Sep 26, 2020
fb85c03

Update requirements.txt


cclauss Sep 26, 2020
35134bf

Update .travis.yml


cclauss Sep 26, 2020
d5b182a

Update requirements.txt


cclauss Sep 26, 2020

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9 changes: 8 additions & 1 deletion
.travis.yml

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Original file line numberDiff line numberDiff line change
@@ -1,7 +1,14 @@
os: linux
dist: focal
addons: # TEMPORARY: Just for Python 3.9-rc2
 apt:
 update: true
 packages:
 - python3-keras
 - python3-pandas
 - python3-sklearn
language: python
python: 3.8
python: 3.9-dev
cache: pip
before_install: pip install --upgrade pip setuptools six
install: pip install black flake8
Expand Down

1 change: 1 addition & 0 deletions
DIRECTORY.md

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Original file line numberDiff line numberDiff line change
Expand Up@@ -319,6 +319,7 @@
 * [Data Transformations](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/data_transformations.py)
 * [Decision Tree](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/decision_tree.py)
 * [Gaussian Naive Bayes](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gaussian_naive_bayes.py)
 * [Gradient Boosting Regressor](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_boosting_regressor.py)
 * [Gradient Descent](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_descent.py)
 * [K Means Clust](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_means_clust.py)
 * [K Nearest Neighbours](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_nearest_neighbours.py)
Expand Down

12 changes: 4 additions & 8 deletions
machine_learning/gradient_boosting_regressor.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -3,11 +3,11 @@
 predict house price.
"""

import pandas as pd
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.datasets import load_boston
from sklearn.metrics import mean_squared_error, r2_score
from sklearn.ensemble import GradientBoostingRegressor
from sklearn.metrics import mean_squared_error, r2_score
from sklearn.model_selection import train_test_split


Expand DownExpand Up@@ -42,10 +42,7 @@ def main():
 training_score = model.score(X_train, y_train).round(3)
 test_score = model.score(X_test, y_test).round(3)
 print("Training score of GradientBoosting is :", training_score)
 print(
 "The test score of GradientBoosting is :",
 test_score
 )
 print("The test score of GradientBoosting is :", test_score)
 # Let us evaluation the model by finding the errors
 y_pred = model.predict(X_test)

Expand All@@ -57,8 +54,7 @@ def main():
 # So let's run the model against the test data
 fig, ax = plt.subplots()
 ax.scatter(y_test, y_pred, edgecolors=(0, 0, 0))
 ax.plot([y_test.min(), y_test.max()],
 [y_test.min(), y_test.max()], "k--", lw=4)
 ax.plot([y_test.min(), y_test.max()], [y_test.min(), y_test.max()], "k--", lw=4)
 ax.set_xlabel("Actual")
 ax.set_ylabel("Predicted")
 ax.set_title("Truth vs Predicted")
Expand Down

12 changes: 6 additions & 6 deletions
requirements.txt

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Original file line numberDiff line numberDiff line change
Expand Up@@ -2,19 +2,19 @@ beautifulsoup4
black
fake_useragent
flake8
keras
keras; python_version <= '3.8'
lxml
matplotlib
mypy
numpy
opencv-python
pandas
pandas; python_version <= '3.8'
pillow
pytest
pytest-cov
requests
scikit-fuzzy
sklearn
scikit-fuzzy; python_version <= '3.8'
sklearn; python_version <= '3.8'
sympy
tensorflow
xgboost
tensorflow; python_version <= '3.8'
xgboost; python_version <= '3.8'