Enables PAVCalibratorPerceptronTest#230

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Enables PAVCalibratorPerceptronTest #230

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58 changes: 58 additions & 0 deletions ...SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration-out.txt
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Original file line numberDiff line numberDiff line change
@@ -0,0 +1,58 @@
maml.exe CV threads=- cali=PAV dout=%Output% data=%Data% seed=1
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
Warning: Skipped 8 instances with missing features during training (over 1 iterations; 8 inst/iter)
Training calibrator.
PAV calibrator: piecewise function approximation has 6 components.
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
Warning: Skipped 8 instances with missing features during training (over 1 iterations; 8 inst/iter)
Training calibrator.
PAV calibrator: piecewise function approximation has 6 components.
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
TEST POSITIVE RATIO: 0.3785 (134.0/(134.0+220.0))
Confusion table
||======================
PREDICTED || positive | negative | Recall
TRUTH ||======================
positive || 132 | 2 | 0.9851
negative || 9 | 211 | 0.9591
||======================
Precision || 0.9362 | 0.9906 |
OVERALL 0/1 ACCURACY: 0.968927
LOG LOSS/instance: Infinity
Test-set entropy (prior Log-Loss/instance): 0.956998
LOG-LOSS REDUCTION (RIG): -Infinity
AUC: 0.992809
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
TEST POSITIVE RATIO: 0.3191 (105.0/(105.0+224.0))
Confusion table
||======================
PREDICTED || positive | negative | Recall
TRUTH ||======================
positive || 102 | 3 | 0.9714
negative || 4 | 220 | 0.9821
||======================
Precision || 0.9623 | 0.9865 |
OVERALL 0/1 ACCURACY: 0.978723
LOG LOSS/instance: 0.239330
Test-set entropy (prior Log-Loss/instance): 0.903454
LOG-LOSS REDUCTION (RIG): 73.509473
AUC: 0.997279

OVERALL RESULTS
---------------------------------------
AUC: 0.995044 (0.0022)
Accuracy: 0.973825 (0.0049)
Positive precision: 0.949217 (0.0130)
Positive recall: 0.978252 (0.0068)
Negative precision: 0.988579 (0.0020)
Negative recall: 0.970617 (0.0115)
Log-loss: Infinity (NaN)
Log-loss reduction: -Infinity (NaN)
F1 Score: 0.963412 (0.0034)
AUPRC: 0.990172 (0.0037)

---------------------------------------
Physical memory usage(MB): %Number%
Virtual memory usage(MB): %Number%
%DateTime% Time elapsed(s): %Number%

4 changes: 4 additions & 0 deletions .../SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration-rp.txt
View file
Open in desktop
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,4 @@
AveragedPerceptron
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
0.995044 0.973825 0.949217 0.978252 0.988579 0.970617 Infinity -Infinity 0.963412 0.990172 AveragedPerceptron %Data% %Output% 99 0 0 maml.exe CV threads=- cali=PAV dout=%Output% data=%Data% seed=1

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n 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;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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Enables PAVCalibratorPerceptronTest#230

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Enables PAVCalibratorPerceptronTest
#230
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f7587de

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58 changes: 58 additions & 0 deletions
...SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration-out.txt

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Original file line numberDiff line numberDiff line change
@@ -0,0 +1,58 @@
maml.exe CV threads=- cali=PAV dout=%Output% data=%Data% seed=1
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
Warning: Skipped 8 instances with missing features during training (over 1 iterations; 8 inst/iter)
Training calibrator.
PAV calibrator: piecewise function approximation has 6 components.
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
Warning: Skipped 8 instances with missing features during training (over 1 iterations; 8 inst/iter)
Training calibrator.
PAV calibrator: piecewise function approximation has 6 components.
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
TEST POSITIVE RATIO:	0.3785 (134.0/(134.0+220.0))
Confusion table
 ||======================
PREDICTED || positive | negative | Recall
TRUTH ||======================
 positive || 132 | 2 | 0.9851
 negative || 9 | 211 | 0.9591
 ||======================
Precision || 0.9362 | 0.9906 |
OVERALL 0/1 ACCURACY: 0.968927
LOG LOSS/instance: Infinity
Test-set entropy (prior Log-Loss/instance): 0.956998
LOG-LOSS REDUCTION (RIG): -Infinity
AUC: 0.992809
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
TEST POSITIVE RATIO:	0.3191 (105.0/(105.0+224.0))
Confusion table
 ||======================
PREDICTED || positive | negative | Recall
TRUTH ||======================
 positive || 102 | 3 | 0.9714
 negative || 4 | 220 | 0.9821
 ||======================
Precision || 0.9623 | 0.9865 |
OVERALL 0/1 ACCURACY: 0.978723
LOG LOSS/instance: 0.239330
Test-set entropy (prior Log-Loss/instance): 0.903454
LOG-LOSS REDUCTION (RIG): 73.509473
AUC: 0.997279

OVERALL RESULTS
---------------------------------------
AUC: 0.995044 (0.0022)
Accuracy: 0.973825 (0.0049)
Positive precision: 0.949217 (0.0130)
Positive recall: 0.978252 (0.0068)
Negative precision: 0.988579 (0.0020)
Negative recall: 0.970617 (0.0115)
Log-loss: Infinity (NaN)
Log-loss reduction: -Infinity (NaN)
F1 Score: 0.963412 (0.0034)
AUPRC: 0.990172 (0.0037)

---------------------------------------
Physical memory usage(MB): %Number%
Virtual memory usage(MB): %Number%
%DateTime% Time elapsed(s): %Number%


4 changes: 4 additions & 0 deletions
.../SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration-rp.txt

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Open in desktop

Original file line numberDiff line numberDiff line change
@@ -0,0 +1,4 @@
AveragedPerceptron
AUC	Accuracy	Positive precision	Positive recall	Negative precision	Negative recall	Log-loss	Log-loss reduction	F1 Score	AUPRC	Learner Name	Train Dataset	Test Dataset	Results File	Run Time	Physical Memory	Virtual Memory	Command Line	Settings	
0.995044	0.973825	0.949217	0.978252	0.988579	0.970617	Infinity	-Infinity	0.963412	0.990172	AveragedPerceptron	%Data% %Output%	99	0	0	maml.exe CV threads=- cali=PAV dout=%Output% data=%Data% seed=1 

Loading

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

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Enables PAVCalibratorPerceptronTest#230

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Enables PAVCalibratorPerceptronTest
#230
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bb252e7

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ec06218

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d3842a0

Added release zbaselines


Anipik May 24, 2018
f7587de

Test Enabled


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ac1797b

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58 changes: 58 additions & 0 deletions
...SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration-out.txt

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Open in desktop

Original file line numberDiff line numberDiff line change
@@ -0,0 +1,58 @@
maml.exe CV threads=- cali=PAV dout=%Output% data=%Data% seed=1
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
Warning: Skipped 8 instances with missing features during training (over 1 iterations; 8 inst/iter)
Training calibrator.
PAV calibrator: piecewise function approximation has 6 components.
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
Warning: Skipped 8 instances with missing features during training (over 1 iterations; 8 inst/iter)
Training calibrator.
PAV calibrator: piecewise function approximation has 6 components.
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
TEST POSITIVE RATIO:	0.3785 (134.0/(134.0+220.0))
Confusion table
 ||======================
PREDICTED || positive | negative | Recall
TRUTH ||======================
 positive || 132 | 2 | 0.9851
 negative || 9 | 211 | 0.9591
 ||======================
Precision || 0.9362 | 0.9906 |
OVERALL 0/1 ACCURACY: 0.968927
LOG LOSS/instance: Infinity
Test-set entropy (prior Log-Loss/instance): 0.956998
LOG-LOSS REDUCTION (RIG): -Infinity
AUC: 0.992809
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
TEST POSITIVE RATIO:	0.3191 (105.0/(105.0+224.0))
Confusion table
 ||======================
PREDICTED || positive | negative | Recall
TRUTH ||======================
 positive || 102 | 3 | 0.9714
 negative || 4 | 220 | 0.9821
 ||======================
Precision || 0.9623 | 0.9865 |
OVERALL 0/1 ACCURACY: 0.978723
LOG LOSS/instance: 0.239330
Test-set entropy (prior Log-Loss/instance): 0.903454
LOG-LOSS REDUCTION (RIG): 73.509473
AUC: 0.997279

OVERALL RESULTS
---------------------------------------
AUC: 0.995044 (0.0022)
Accuracy: 0.973825 (0.0049)
Positive precision: 0.949217 (0.0130)
Positive recall: 0.978252 (0.0068)
Negative precision: 0.988579 (0.0020)
Negative recall: 0.970617 (0.0115)
Log-loss: Infinity (NaN)
Log-loss reduction: -Infinity (NaN)
F1 Score: 0.963412 (0.0034)
AUPRC: 0.990172 (0.0037)

---------------------------------------
Physical memory usage(MB): %Number%
Virtual memory usage(MB): %Number%
%DateTime% Time elapsed(s): %Number%


4 changes: 4 additions & 0 deletions
.../SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration-rp.txt

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -0,0 +1,4 @@
AveragedPerceptron
AUC	Accuracy	Positive precision	Positive recall	Negative precision	Negative recall	Log-loss	Log-loss reduction	F1 Score	AUPRC	Learner Name	Train Dataset	Test Dataset	Results File	Run Time	Physical Memory	Virtual Memory	Command Line	Settings	
0.995044	0.973825	0.949217	0.978252	0.988579	0.970617	Infinity	-Infinity	0.963412	0.990172	AveragedPerceptron	%Data% %Output%	99	0	0	maml.exe CV threads=- cali=PAV dout=%Output% data=%Data% seed=1 

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

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Enables PAVCalibratorPerceptronTest#230

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 Closed

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Enables PAVCalibratorPerceptronTest
#230
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bb252e7

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ec06218

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d3842a0

Added release zbaselines


Anipik May 24, 2018
f7587de

Test Enabled


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ac1797b

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58 changes: 58 additions & 0 deletions
...SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration-out.txt

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Open in desktop

Original file line numberDiff line numberDiff line change
@@ -0,0 +1,58 @@
maml.exe CV threads=- cali=PAV dout=%Output% data=%Data% seed=1
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
Warning: Skipped 8 instances with missing features during training (over 1 iterations; 8 inst/iter)
Training calibrator.
PAV calibrator: piecewise function approximation has 6 components.
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
Warning: Skipped 8 instances with missing features during training (over 1 iterations; 8 inst/iter)
Training calibrator.
PAV calibrator: piecewise function approximation has 6 components.
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
TEST POSITIVE RATIO:	0.3785 (134.0/(134.0+220.0))
Confusion table
 ||======================
PREDICTED || positive | negative | Recall
TRUTH ||======================
 positive || 132 | 2 | 0.9851
 negative || 9 | 211 | 0.9591
 ||======================
Precision || 0.9362 | 0.9906 |
OVERALL 0/1 ACCURACY: 0.968927
LOG LOSS/instance: Infinity
Test-set entropy (prior Log-Loss/instance): 0.956998
LOG-LOSS REDUCTION (RIG): -Infinity
AUC: 0.992809
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
TEST POSITIVE RATIO:	0.3191 (105.0/(105.0+224.0))
Confusion table
 ||======================
PREDICTED || positive | negative | Recall
TRUTH ||======================
 positive || 102 | 3 | 0.9714
 negative || 4 | 220 | 0.9821
 ||======================
Precision || 0.9623 | 0.9865 |
OVERALL 0/1 ACCURACY: 0.978723
LOG LOSS/instance: 0.239330
Test-set entropy (prior Log-Loss/instance): 0.903454
LOG-LOSS REDUCTION (RIG): 73.509473
AUC: 0.997279

OVERALL RESULTS
---------------------------------------
AUC: 0.995044 (0.0022)
Accuracy: 0.973825 (0.0049)
Positive precision: 0.949217 (0.0130)
Positive recall: 0.978252 (0.0068)
Negative precision: 0.988579 (0.0020)
Negative recall: 0.970617 (0.0115)
Log-loss: Infinity (NaN)
Log-loss reduction: -Infinity (NaN)
F1 Score: 0.963412 (0.0034)
AUPRC: 0.990172 (0.0037)

---------------------------------------
Physical memory usage(MB): %Number%
Virtual memory usage(MB): %Number%
%DateTime% Time elapsed(s): %Number%


4 changes: 4 additions & 0 deletions
.../SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration-rp.txt

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Open in desktop

Original file line numberDiff line numberDiff line change
@@ -0,0 +1,4 @@
AveragedPerceptron
AUC	Accuracy	Positive precision	Positive recall	Negative precision	Negative recall	Log-loss	Log-loss reduction	F1 Score	AUPRC	Learner Name	Train Dataset	Test Dataset	Results File	Run Time	Physical Memory	Virtual Memory	Command Line	Settings	
0.995044	0.973825	0.949217	0.978252	0.988579	0.970617	Infinity	-Infinity	0.963412	0.990172	AveragedPerceptron	%Data% %Output%	99	0	0	maml.exe CV threads=- cali=PAV dout=%Output% data=%Data% seed=1 

Loading

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

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Enables PAVCalibratorPerceptronTest#230

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 Closed

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Enables PAVCalibratorPerceptronTest
#230
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bb252e7

Test Enabled


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ec06218

Added Debug Files


Anipik May 24, 2018
d3842a0

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...SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration-out.txt

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Original file line numberDiff line numberDiff line change
@@ -0,0 +1,58 @@
maml.exe CV threads=- cali=PAV dout=%Output% data=%Data% seed=1
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
Warning: Skipped 8 instances with missing features during training (over 1 iterations; 8 inst/iter)
Training calibrator.
PAV calibrator: piecewise function approximation has 6 components.
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
Warning: Skipped 8 instances with missing features during training (over 1 iterations; 8 inst/iter)
Training calibrator.
PAV calibrator: piecewise function approximation has 6 components.
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
TEST POSITIVE RATIO:	0.3785 (134.0/(134.0+220.0))
Confusion table
 ||======================
PREDICTED || positive | negative | Recall
TRUTH ||======================
 positive || 132 | 2 | 0.9851
 negative || 9 | 211 | 0.9591
 ||======================
Precision || 0.9362 | 0.9906 |
OVERALL 0/1 ACCURACY: 0.968927
LOG LOSS/instance: Infinity
Test-set entropy (prior Log-Loss/instance): 0.956998
LOG-LOSS REDUCTION (RIG): -Infinity
AUC: 0.992809
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
TEST POSITIVE RATIO:	0.3191 (105.0/(105.0+224.0))
Confusion table
 ||======================
PREDICTED || positive | negative | Recall
TRUTH ||======================
 positive || 102 | 3 | 0.9714
 negative || 4 | 220 | 0.9821
 ||======================
Precision || 0.9623 | 0.9865 |
OVERALL 0/1 ACCURACY: 0.978723
LOG LOSS/instance: 0.239330
Test-set entropy (prior Log-Loss/instance): 0.903454
LOG-LOSS REDUCTION (RIG): 73.509473
AUC: 0.997279

OVERALL RESULTS
---------------------------------------
AUC: 0.995044 (0.0022)
Accuracy: 0.973825 (0.0049)
Positive precision: 0.949217 (0.0130)
Positive recall: 0.978252 (0.0068)
Negative precision: 0.988579 (0.0020)
Negative recall: 0.970617 (0.0115)
Log-loss: Infinity (NaN)
Log-loss reduction: -Infinity (NaN)
F1 Score: 0.963412 (0.0034)
AUPRC: 0.990172 (0.0037)

---------------------------------------
Physical memory usage(MB): %Number%
Virtual memory usage(MB): %Number%
%DateTime% Time elapsed(s): %Number%


4 changes: 4 additions & 0 deletions
.../SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration-rp.txt

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -0,0 +1,4 @@
AveragedPerceptron
AUC	Accuracy	Positive precision	Positive recall	Negative precision	Negative recall	Log-loss	Log-loss reduction	F1 Score	AUPRC	Learner Name	Train Dataset	Test Dataset	Results File	Run Time	Physical Memory	Virtual Memory	Command Line	Settings	
0.995044	0.973825	0.949217	0.978252	0.988579	0.970617	Infinity	-Infinity	0.963412	0.990172	AveragedPerceptron	%Data% %Output%	99	0	0	maml.exe CV threads=- cali=PAV dout=%Output% data=%Data% seed=1 

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

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Enables PAVCalibratorPerceptronTest#230

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Enables PAVCalibratorPerceptronTest
#230
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d3842a0

Added release zbaselines


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58 changes: 58 additions & 0 deletions
...SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration-out.txt

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Original file line numberDiff line numberDiff line change
@@ -0,0 +1,58 @@
maml.exe CV threads=- cali=PAV dout=%Output% data=%Data% seed=1
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
Warning: Skipped 8 instances with missing features during training (over 1 iterations; 8 inst/iter)
Training calibrator.
PAV calibrator: piecewise function approximation has 6 components.
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
Warning: Skipped 8 instances with missing features during training (over 1 iterations; 8 inst/iter)
Training calibrator.
PAV calibrator: piecewise function approximation has 6 components.
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
TEST POSITIVE RATIO:	0.3785 (134.0/(134.0+220.0))
Confusion table
 ||======================
PREDICTED || positive | negative | Recall
TRUTH ||======================
 positive || 132 | 2 | 0.9851
 negative || 9 | 211 | 0.9591
 ||======================
Precision || 0.9362 | 0.9906 |
OVERALL 0/1 ACCURACY: 0.968927
LOG LOSS/instance: Infinity
Test-set entropy (prior Log-Loss/instance): 0.956998
LOG-LOSS REDUCTION (RIG): -Infinity
AUC: 0.992809
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
TEST POSITIVE RATIO:	0.3191 (105.0/(105.0+224.0))
Confusion table
 ||======================
PREDICTED || positive | negative | Recall
TRUTH ||======================
 positive || 102 | 3 | 0.9714
 negative || 4 | 220 | 0.9821
 ||======================
Precision || 0.9623 | 0.9865 |
OVERALL 0/1 ACCURACY: 0.978723
LOG LOSS/instance: 0.239330
Test-set entropy (prior Log-Loss/instance): 0.903454
LOG-LOSS REDUCTION (RIG): 73.509473
AUC: 0.997279

OVERALL RESULTS
---------------------------------------
AUC: 0.995044 (0.0022)
Accuracy: 0.973825 (0.0049)
Positive precision: 0.949217 (0.0130)
Positive recall: 0.978252 (0.0068)
Negative precision: 0.988579 (0.0020)
Negative recall: 0.970617 (0.0115)
Log-loss: Infinity (NaN)
Log-loss reduction: -Infinity (NaN)
F1 Score: 0.963412 (0.0034)
AUPRC: 0.990172 (0.0037)

---------------------------------------
Physical memory usage(MB): %Number%
Virtual memory usage(MB): %Number%
%DateTime% Time elapsed(s): %Number%


4 changes: 4 additions & 0 deletions
.../SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration-rp.txt

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -0,0 +1,4 @@
AveragedPerceptron
AUC	Accuracy	Positive precision	Positive recall	Negative precision	Negative recall	Log-loss	Log-loss reduction	F1 Score	AUPRC	Learner Name	Train Dataset	Test Dataset	Results File	Run Time	Physical Memory	Virtual Memory	Command Line	Settings	
0.995044	0.973825	0.949217	0.978252	0.988579	0.970617	Infinity	-Infinity	0.963412	0.990172	AveragedPerceptron	%Data% %Output%	99	0	0	maml.exe CV threads=- cali=PAV dout=%Output% data=%Data% seed=1 

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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Enables PAVCalibratorPerceptronTest#230

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Enables PAVCalibratorPerceptronTest
#230
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bb252e7

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ec06218

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d3842a0

Added release zbaselines


Anipik May 24, 2018
f7587de

Test Enabled


Anipik May 24, 2018
ac1797b

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58 changes: 58 additions & 0 deletions
...SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration-out.txt

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Open in desktop

Original file line numberDiff line numberDiff line change
@@ -0,0 +1,58 @@
maml.exe CV threads=- cali=PAV dout=%Output% data=%Data% seed=1
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
Warning: Skipped 8 instances with missing features during training (over 1 iterations; 8 inst/iter)
Training calibrator.
PAV calibrator: piecewise function approximation has 6 components.
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
Warning: Skipped 8 instances with missing features during training (over 1 iterations; 8 inst/iter)
Training calibrator.
PAV calibrator: piecewise function approximation has 6 components.
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
TEST POSITIVE RATIO:	0.3785 (134.0/(134.0+220.0))
Confusion table
 ||======================
PREDICTED || positive | negative | Recall
TRUTH ||======================
 positive || 132 | 2 | 0.9851
 negative || 9 | 211 | 0.9591
 ||======================
Precision || 0.9362 | 0.9906 |
OVERALL 0/1 ACCURACY: 0.968927
LOG LOSS/instance: Infinity
Test-set entropy (prior Log-Loss/instance): 0.956998
LOG-LOSS REDUCTION (RIG): -Infinity
AUC: 0.992809
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
TEST POSITIVE RATIO:	0.3191 (105.0/(105.0+224.0))
Confusion table
 ||======================
PREDICTED || positive | negative | Recall
TRUTH ||======================
 positive || 102 | 3 | 0.9714
 negative || 4 | 220 | 0.9821
 ||======================
Precision || 0.9623 | 0.9865 |
OVERALL 0/1 ACCURACY: 0.978723
LOG LOSS/instance: 0.239330
Test-set entropy (prior Log-Loss/instance): 0.903454
LOG-LOSS REDUCTION (RIG): 73.509473
AUC: 0.997279

OVERALL RESULTS
---------------------------------------
AUC: 0.995044 (0.0022)
Accuracy: 0.973825 (0.0049)
Positive precision: 0.949217 (0.0130)
Positive recall: 0.978252 (0.0068)
Negative precision: 0.988579 (0.0020)
Negative recall: 0.970617 (0.0115)
Log-loss: Infinity (NaN)
Log-loss reduction: -Infinity (NaN)
F1 Score: 0.963412 (0.0034)
AUPRC: 0.990172 (0.0037)

---------------------------------------
Physical memory usage(MB): %Number%
Virtual memory usage(MB): %Number%
%DateTime% Time elapsed(s): %Number%


4 changes: 4 additions & 0 deletions
.../SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration-rp.txt

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -0,0 +1,4 @@
AveragedPerceptron
AUC	Accuracy	Positive precision	Positive recall	Negative precision	Negative recall	Log-loss	Log-loss reduction	F1 Score	AUPRC	Learner Name	Train Dataset	Test Dataset	Results File	Run Time	Physical Memory	Virtual Memory	Command Line	Settings	
0.995044	0.973825	0.949217	0.978252	0.988579	0.970617	Infinity	-Infinity	0.963412	0.990172	AveragedPerceptron	%Data% %Output%	99	0	0	maml.exe CV threads=- cali=PAV dout=%Output% data=%Data% seed=1 

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

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Enables PAVCalibratorPerceptronTest#230

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 Closed

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Enables PAVCalibratorPerceptronTest
#230
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bb252e7

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ec06218

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Anipik May 24, 2018
d3842a0

Added release zbaselines


Anipik May 24, 2018
f7587de

Test Enabled


Anipik May 24, 2018
ac1797b

Debug files added


Anipik May 24, 2018
0b1d519

Release Files Added


Anipik May 24, 2018

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58 changes: 58 additions & 0 deletions
...SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration-out.txt

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Open in desktop

Original file line numberDiff line numberDiff line change
@@ -0,0 +1,58 @@
maml.exe CV threads=- cali=PAV dout=%Output% data=%Data% seed=1
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
Warning: Skipped 8 instances with missing features during training (over 1 iterations; 8 inst/iter)
Training calibrator.
PAV calibrator: piecewise function approximation has 6 components.
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
Warning: Skipped 8 instances with missing features during training (over 1 iterations; 8 inst/iter)
Training calibrator.
PAV calibrator: piecewise function approximation has 6 components.
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
TEST POSITIVE RATIO:	0.3785 (134.0/(134.0+220.0))
Confusion table
 ||======================
PREDICTED || positive | negative | Recall
TRUTH ||======================
 positive || 132 | 2 | 0.9851
 negative || 9 | 211 | 0.9591
 ||======================
Precision || 0.9362 | 0.9906 |
OVERALL 0/1 ACCURACY: 0.968927
LOG LOSS/instance: Infinity
Test-set entropy (prior Log-Loss/instance): 0.956998
LOG-LOSS REDUCTION (RIG): -Infinity
AUC: 0.992809
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
TEST POSITIVE RATIO:	0.3191 (105.0/(105.0+224.0))
Confusion table
 ||======================
PREDICTED || positive | negative | Recall
TRUTH ||======================
 positive || 102 | 3 | 0.9714
 negative || 4 | 220 | 0.9821
 ||======================
Precision || 0.9623 | 0.9865 |
OVERALL 0/1 ACCURACY: 0.978723
LOG LOSS/instance: 0.239330
Test-set entropy (prior Log-Loss/instance): 0.903454
LOG-LOSS REDUCTION (RIG): 73.509473
AUC: 0.997279

OVERALL RESULTS
---------------------------------------
AUC: 0.995044 (0.0022)
Accuracy: 0.973825 (0.0049)
Positive precision: 0.949217 (0.0130)
Positive recall: 0.978252 (0.0068)
Negative precision: 0.988579 (0.0020)
Negative recall: 0.970617 (0.0115)
Log-loss: Infinity (NaN)
Log-loss reduction: -Infinity (NaN)
F1 Score: 0.963412 (0.0034)
AUPRC: 0.990172 (0.0037)

---------------------------------------
Physical memory usage(MB): %Number%
Virtual memory usage(MB): %Number%
%DateTime% Time elapsed(s): %Number%


4 changes: 4 additions & 0 deletions
.../SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration-rp.txt

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -0,0 +1,4 @@
AveragedPerceptron
AUC	Accuracy	Positive precision	Positive recall	Negative precision	Negative recall	Log-loss	Log-loss reduction	F1 Score	AUPRC	Learner Name	Train Dataset	Test Dataset	Results File	Run Time	Physical Memory	Virtual Memory	Command Line	Settings	
0.995044	0.973825	0.949217	0.978252	0.988579	0.970617	Infinity	-Infinity	0.963412	0.990172	AveragedPerceptron	%Data% %Output%	99	0	0	maml.exe CV threads=- cali=PAV dout=%Output% data=%Data% seed=1 

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