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Logging.html
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<!DOCTYPE html>
<head>
<style>
table { width: 100% }
th { font:bold 10pt Tahoma; }
td { font:normal 10pt Tahoma; }
h1 {font:normal 11pt Tahoma;}
</style>
</head>
<body>
<h1>Sun Oct 13 15:39:15 EDT 2019</h1>
<table border="0" cellpadding="5" cellspacing="3">
<tr align="left">
<th style="width:10%">Loglevel</th>
<th style="width:15%">Time</th>
<th style="width:75%">Log Message</th>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>GET: /predicttest</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>POST: /predicttest</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>annot: all_type</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>predictedLabel: all_type</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>algo: logistic</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Training file dir: C:\Users\Jiuning\Documents\Python Scripts\LightSideWB\testData/Train_all_types.csv</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Completed process of load file</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>invoking 4 tasks...</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 0 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 3 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 1 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 2 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Parallel extraction complete in 0.0 seconds.
</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>invoking 4 tasks...</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 1 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 0 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 2 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 3 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Parallel extraction complete in 6.9 seconds.
</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>size of hits205499</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Number of features extracted:5369</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Created Feature Extraction!!</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>BuildModelControl KEY: foldMethod value: AUTO</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>BuildModelControl KEY: numFolds value: 10</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>BuildModelControl KEY: source value: RANDOM</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>BuildModelControl KEY: test value: true</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>BuildModelControl KEY: testRecipe value: Train_all_types.csv</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>BuildModelControl KEY: testSet value: edu.cmu.side.model.data.DocumentList@9299f8b</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>BuildModelControl KEY: type value: CV</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>training table size:1545</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Training new model.</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>here!</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>size of learner settings:2</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>{foldMethod=AUTO, numFolds=10, source=RANDOM, test=true, testRecipe=Train_all_types.csv, testSet=edu.cmu.side.model.data.DocumentList@9299f8b, type=CV}</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>edu.cmu.side.model.OrderedPluginMap@3ffb585d</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>learner:Logistic Regression</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>updater:edu.cmu.side.view.util.ParallelTaskUpdater[,0,0,0x0,invalid,layout=se.datadosen.component.RiverLayout,alignmentX=0.0,alignmentY=0.0,border=,flags=9,maximumSize=,minimumSize=java.awt.Dimension[width=200,height=20],preferredSize=]</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>trained size:1545</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Fetched Results successfully</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>confusion matrix key set: 4</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Text Confusion Matrix: L-IL-IS L-Q L-R
L-I1138 0 0 1
L-IS 8 0 1 0
L-Q 226 0 70 1
L-R 69 0 1 30
</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Evaluation: 1545</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Model Evaluation Matrix</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>{Accuracy=0.801294498381877, Kappa=0.34227239572788704, }</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>0.801294498381877</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>requestID: 123456</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>JSON: the northern lights happen when the sun makes tiny bits of electricity go down to earth</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>annot: all_type</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>recipelist size: 1</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>invoking 1 tasks...</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 0 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Parallel extraction complete in 0.0 seconds.
</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>invoking 1 tasks...</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 0 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Parallel extraction complete in 0.0 seconds.
</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Feature Density Mean: 1.0227272727272727</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Feature Density Deviation: 0.0</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>WekaCore: loading classifier from settings... </td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>WekaCore: done loading classifier in 442ms</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Predicted Label: PredictedTestData Predicted Label likelihood: L-I</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Predicted Label: PredictedTestData_L-I Predicted Label likelihood: 0.8510961723298188</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Predicted Label: PredictedTestData_L-IS Predicted Label likelihood: 2.8123547718580537E-4</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Predicted Label: PredictedTestData_L-Q Predicted Label likelihood: 0.11832851667590386</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Predicted Label: PredictedTestData_L-R Predicted Label likelihood: 0.030294075517091623</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Predicted Label: all_type Predicted Label likelihood: </td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Predicted Label1: PredictedTestData_L-I Predicted Label1: PredictedTestData_L-IS</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Predicted Label1 likelihood: 0.8510961723298188 Predicted Label2 likelihood: 2.8123547718580537E-4</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>annot: Complexity_level</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>predictedLabel: Complexity_level</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>algo: logistic</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Training file dir: C:\Users\Jiuning\Documents\Python Scripts\LightSideWB\testData/Train_KF2.csv</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Completed process of load file</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>invoking 4 tasks...</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 1 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 0 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 2 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 3 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Parallel extraction complete in 2.3 seconds.
</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>invoking 4 tasks...</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 0 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 2 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 1 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 3 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Parallel extraction complete in 0.0 seconds.
</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>size of hits160250</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Number of features extracted:4336</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Created Feature Extraction!!</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>BuildModelControl KEY: foldMethod value: AUTO</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>BuildModelControl KEY: numFolds value: 10</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>BuildModelControl KEY: source value: RANDOM</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>BuildModelControl KEY: test value: true</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>BuildModelControl KEY: testRecipe value: Train_KF2.csv</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>BuildModelControl KEY: testSet value: edu.cmu.side.model.data.DocumentList@e02dd30</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>BuildModelControl KEY: type value: CV</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>training table size:1139</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Training new model.</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>here!</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>size of learner settings:2</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>{foldMethod=AUTO, numFolds=10, source=RANDOM, test=true, testRecipe=Train_KF2.csv, testSet=edu.cmu.side.model.data.DocumentList@e02dd30, type=CV}</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>edu.cmu.side.model.OrderedPluginMap@4d373d7</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>learner:Logistic Regression</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>updater:edu.cmu.side.view.util.ParallelTaskUpdater[,0,0,0x0,invalid,layout=se.datadosen.component.RiverLayout,alignmentX=0.0,alignmentY=0.0,border=,flags=9,maximumSize=,minimumSize=java.awt.Dimension[width=200,height=20],preferredSize=]</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>trained size:1139</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Fetched Results successfully</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>confusion matrix key set: 2</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Text Confusion Matrix: L-T L-X
L-T 456 126
L-X 133 424
</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Evaluation: 1139</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Model Evaluation Matrix</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>{Accuracy=0.7726075504828798, Kappa=0.5448730508675925, }</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>0.7726075504828798</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>requestID: 123456</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>JSON: the northern lights happen when the sun makes tiny bits of electricity go down to earth</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>annot: Complexity_level</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>recipelist size: 1</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>invoking 1 tasks...</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 0 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Parallel extraction complete in 0.0 seconds.
</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>invoking 1 tasks...</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 0 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Parallel extraction complete in 0.0 seconds.
</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Feature Density Mean: 1.0227272727272727</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Feature Density Deviation: 0.0</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>WekaCore: loading classifier from settings... </td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>WekaCore: done loading classifier in 25ms</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Predicted Label: Complexity_level Predicted Label likelihood: </td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Predicted Label: PredictedTestData Predicted Label likelihood: L-X</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Predicted Label: PredictedTestData_L-T Predicted Label likelihood: 0.44818845539316665</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Predicted Label: PredictedTestData_L-X Predicted Label likelihood: 0.5518115446068333</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Predicted Label1: PredictedTestData_L-T Predicted Label1: PredictedTestData_L-X</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Predicted Label1 likelihood: 0.44818845539316665 Predicted Label2 likelihood: 0.5518115446068333</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>annot: Complexity_level</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>predictedLabel: Complexity_level</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>algo: logistic</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Training file dir: C:\Users\Jiuning\Documents\Python Scripts\LightSideWB\testData/Train_KF_X.csv</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Completed process of load file</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>invoking 4 tasks...</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 1 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 0 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 2 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 3 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Parallel extraction complete in 0.7 seconds.
</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>invoking 4 tasks...</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 0 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 3 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 1 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 2 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Parallel extraction complete in 0.0 seconds.
</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>size of hits95388</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Number of features extracted:2842</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Created Feature Extraction!!</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>BuildModelControl KEY: foldMethod value: AUTO</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>BuildModelControl KEY: numFolds value: 10</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>BuildModelControl KEY: source value: RANDOM</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>BuildModelControl KEY: test value: true</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>BuildModelControl KEY: testRecipe value: Train_KF_X.csv</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>BuildModelControl KEY: testSet value: edu.cmu.side.model.data.DocumentList@50e69a7a</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>BuildModelControl KEY: type value: CV</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>training table size:557</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Training new model.</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>here!</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>size of learner settings:2</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>{foldMethod=AUTO, numFolds=10, source=RANDOM, test=true, testRecipe=Train_KF_X.csv, testSet=edu.cmu.side.model.data.DocumentList@50e69a7a, type=CV}</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>edu.cmu.side.model.OrderedPluginMap@33d6635e</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>learner:Logistic Regression</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>updater:edu.cmu.side.view.util.ParallelTaskUpdater[,0,0,0x0,invalid,layout=se.datadosen.component.RiverLayout,alignmentX=0.0,alignmentY=0.0,border=,flags=9,maximumSize=,minimumSize=java.awt.Dimension[width=200,height=20],preferredSize=]</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>trained size:557</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Fetched Results successfully</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>confusion matrix key set: 2</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Text Confusion Matrix: L-EL-EE
L-E 386 17
L-EE 92 62
</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Evaluation: 557</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Model Evaluation Matrix</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>{Accuracy=0.8043087971274686, Kappa=0.42424299898529166, }</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>0.8043087971274686</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>requestID: 123456</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>JSON: the northern lights happen when the sun makes tiny bits of electricity go down to earth</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>annot: Complexity_level</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>recipelist size: 1</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>invoking 1 tasks...</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 0 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Parallel extraction complete in 0.0 seconds.
</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>invoking 1 tasks...</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Thread 0 complete.</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>Parallel extraction complete in 0.0 seconds.
</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Feature Density Mean: 1.0227272727272727</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Feature Density Deviation: 0.0</td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>WekaCore: loading classifier from settings... </td>
</tr>
<tr>
<td>FINE</td>
<td>Oct 13,2019 15:39</td>
<td>WekaCore: done loading classifier in 13ms</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Predicted Label: Complexity_level Predicted Label likelihood: </td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Predicted Label: PredictedTestData Predicted Label likelihood: L-E</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Predicted Label: PredictedTestData_L-E Predicted Label likelihood: 0.86199605202059</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Predicted Label: PredictedTestData_L-EE Predicted Label likelihood: 0.13800394797940996</td>
</tr>
<tr>
<td>INFO</td>
<td>Oct 13,2019 15:39</td>
<td>Predicted Label1: PredictedTestData_L-E Predicted Label1: PredictedTestData_L-EE</td>
</tr>