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BigMLer report subcommand: ROC curve and metrics graph for bigmler analyze --nodes
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<!DOCTYPE html>
<meta charset="utf-8">
<style>
html, body{
height: 100%;
}
*, *:before, *:after {
-webkit-box-sizing: border-box;
-moz-box-sizing: border-box;
box-sizing: border-box;
}
body {
font: 14px/18px "Helvetica Neue", Helvetica, Arial, sans-serif;
margin: 0;
position: relative;
background: #fff;
display: block;
color: #333;
}
.clearfix:after {
visibility: hidden;
display: block;
font-size: 0;
content: " ";
clear: both;
height: 0;
}
.clearfix { display: inline-table; }
* html .clearfix { height: 1%; }
.clearfix { display: block; }
#wrap{
min-height: 100%;
height: auto;
margin: 0 auto -60px;
padding: 0 0 60px;
}
#header{
height: 100px;
background: #F7F7F7;
border-bottom: 1px solid #D6D8D9;
border-top: 4px solid #293A44;
}
#header img{
margin-top: 10px;
}
#footer {
height: 60px;
background-color: #293A43;
color: #5D6F79;
text-align: center;
font-size: 11px;
padding-top: 20px;
float: bottom;
}
.container{
width: 960px;
margin: 0 auto;
padding: 0 30px;
}
#chart {
float: left;
width: 720px;
margin-top: 30px;
}
#metrics_chart {
float: left;
width: 720px;
margin-top: 30px;
}
#metrics {
float: left;
margin-top: 30px;
}
.sliders{
float: left;
width: 170px;
margin-top: 30px;
}
.slider_box{
background: #eee;
padding: 10px 10px 5px;
margin-top:20px;
border-radius:5px;
}
.sliders label{
display: block;
}
.sliders input{
float: left;
margin-bottom: 10px;
}
.sliders .value_slider{
display: block;
font-weight: bold;
text-align: center;
}
.sliders button {
float: left;
background: #eee;
margin-top:20px;
border-radius:5px;
}
.legend{
font-size: 12px;
}
.axis path,
.axis line {
fill: none;
stroke: black;
shape-rendering: crispEdges;
}
.axis text {
font-family: sans-serif;
font-size: 11px;
}
.site-title {
background: url(https://static.bigml.com/static/img/logo_menu.png) no-repeat 0 0 transparent;
margin: 20px 0 0 0;
padding: 17px 0 12px 185px;
color: #25343d;
}
.bottom {
margin-top: 150px;
float: bottom;
height: 70px;
}
.hidden {
display: none;
}
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<body>
<div id="wrap">
<div id="header">
<div class="container clearfix">
<h2 class="site-title"></h2>
</div>
</div>
<div class="container clearfix">
<!-- h3>@@SUBTITLE@@</h3 -->
<div id="ROC_chart" class="hidden">
<div id="chart"></div>
<div class="sliders">
<div class="clearfix slider_box">
<label>Positive class:</label>
<div id="classes"></div>
</div>
<div class="clearfix slider_box">
<label>Iso-cost line:</label>
<input id="isoline" type="range" min="0" max="100" value="20">
</div>
<div class="clearfix slider_box">
<label>P(+):</label>
<input id="prevalence" type="range" min="0" max="40" value="20">
<div id="prevalencedisplay" class="value_slider">0.5</div>
</div>
<div class="clearfix slider_box">
<label>FP cost:</label>
<input id="fpcost" type="range" min="1" max="250" value="25">
<div id="fpcostdisplay" class="value_slider">0.25</div>
</div>
<div class="clearfix slider_box">
<label>FN cost:</label>
<input id="fncost" type="range" min="1" max="250" value="25">
<div id="fncostdisplay" class="value_slider">0.25</div>
</div>
</div>
</div>
<div id="metrics_chart"></div>
<div class="sliders bottom">
<div id="tooltip" class="slider_box"></div>
</div>
</div>
</div>
<div id="footer">
bigmler analyze results - Powered by BigML <br/>
Copyright © 2015 BigML, Inc.
</div>
</body>
<script
src="https://ajax.googleapis.com/ajax/libs/jquery/1.11.3/jquery.min.js">
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<script src="https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.6/d3.min.js"
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<script>
// Computes Area Under the Curve using Heron's formula
var AUC = function(tpr, fpr) {
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b = Math.sqrt(tpr * tpr + fpr * fpr);
c = Math.sqrt((1 - tpr) * (1 - tpr) + (1 - fpr) * (1 - fpr));
s = (a + b + c) /2;
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return 0.5 - Math.sqrt(s * (s - a) * (s - b) * (s - c));
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.text("False Positive Rate");
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<script>
// Loads multiple evaluations
var loadEvaluations = function(options) {
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callback: function() {},
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var s = $('<select id="positiveClass" />');
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settings.positiveClass = $("#positiveClass").val();
svg.selectAll('circle').data([]).exit().remove();
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$.ajax({
url : settings.urls[settings.evaluations.length],
dataType: 'jsonp',
crossDomain:true,
success: function(evaluation) {
processEvaluation(settings, evaluation)
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});
} else {
settings.maxAUC = - Infinity;
for(var i =0;i<settings.evaluations_json.length;i++) {
processEvaluation(settings,
settings.evaluations_ids[i] || undefined,
settings.evaluations_json[i])
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}
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loadEvaluations(settings);
} else {
settings.callback(settings.evaluations,
settings.maxInstances,
settings.maxAUC);
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}
var processEvaluation = function(settings, evaluation_id, evaluation) {
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var positiveClassIndex = evaluation.class_names.indexOf(positiveClass);
var truePositiveRate = falsePositiveRate = 0;
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var tpPlusFN = confusionMatrix[positiveClassIndex].reduce(
function(total, currentValue) {
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});
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truePositiveRate = (
confusionMatrix[positiveClassIndex][positiveClassIndex] /
tpPlusFN);
} else {
truePositiveRate = NaN;
}
var fp = 0
var fpPlusTN = 0
for (var i=0;i<confusionMatrix.length;i++) {
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continue;
fp += confusionMatrix[i][positiveClassIndex]
fpPlusTN += confusionMatrix[i].reduce(
function(total, currentValue, index, array) {
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});
}
if (fpPlusTN != 0) {
falsePositiveRate = fp / fpPlusTN;
} else {
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// settings.maxInstances = evaluation.sampled_rows
//}
settings.maxInstances = 0.5;
result = {
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"resource": evaluation.name,
"fields": evaluation.model_fields,
"nodes": evaluation.nodes,
"tpr": truePositiveRate,
"fpr": falsePositiveRate,
"instances": settings.maxInstances,
"auc": AUC(truePositiveRate, falsePositiveRate)}
if (result.auc > settings.maxAUC) {
settings.maxAUC = result.auc;
}
settings.evaluations.push(result);
};
</script>
<script>
var isocost = 0.2
var prevalence = 0.5
var pcostpcost = 0.25
var fncost = 0.25
var costfp = (1 - prevalence) * fpcost
var costfn = prevalence * fncost
var slope = costfp / costfn;
var updateCostLines= function () {
costfp = (1 - prevalence) * fpcost;
costfn = Math.max(prevalence * fncost, 0.0001);
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d3.select("#prevalence").on("change", function() {
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<script>
var MEASURES = ["accuracy", "precision", "recall", "f_measure", "phi",
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var MIN_MEASURES = ["mean_squared_error", "mean_absolute_error"];
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}
tooltip.transition()
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.style("opacity", .9);
tooltip.html(str)
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d3.select(this).style("cursor", "hand");
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tooltip.transition()
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d3.select(this).style("cursor", "pointer");
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updateData();
})
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d3.select(this).style("cursor", "hand");
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d3.select(this).style("cursor", "pointer");
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});
}
updateData();
</script>>
[{"kfold": 3, "time": 1438642344.476623, "value": 0.5903833333333334, "measure": "accuracy", "directory": "node_th3", "nodes": "3"}, {"kfold": 3, "time": 1438642344.476623, "value": 0.6056366666666667, "measure": "precision", "directory": "node_th3", "nodes": "3"}, {"kfold": 3, "time": 1438642344.476623, "value": 0.5851833333333334, "measure": "recall", "directory": "node_th3", "nodes": "3"}, {"kfold": 3, "time": 1438642344.476623, "value": 0.18617666666666666, "measure": "phi", "directory": "node_th3", "nodes": "3"}, {"kfold": 3, "time": 1438642344.476623, "value": 0.5532766666666667, "measure": "f_measure", "directory": "node_th3", "nodes": "3"}, {"kfold": 8, "time": 1438642376.3286235, "value": 0.6904133333333333, "measure": "accuracy", "directory": "node_th8", "nodes": "8"}, {"kfold": 8, "time": 1438642376.3286235, "value": 0.68049, "measure": "precision", "directory": "node_th8", "nodes": "8"}, {"kfold": 8, "time": 1438642376.3286235, "value": 0.6768066666666668, "measure": 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