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Last active December 15, 2015 15:39
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Adult - Scattergraph (support vs confidence)
<!DOCTYPE html>
<meta charset="utf-8">
<style>
body {
font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
margin: auto;
position: relative;
width: 960px;
background: #fff;
}
text {
font: 10px sans-serif;
}
#chart {
position: absolute;
left: 10px;
top: 10px;
line-height: 150%
}
.axis path,
.axis line {
fill: none;
stroke: black;
shape-rendering: crispEdges;
}
.axis text {
font-family: sans-serif;
font-size: 11px;
}
</style>
<body>
<div id="chart"></div>
</body>
<script src="http://d3js.org/d3.v3.min.js"></script>
<script>
d3.json("model.json", function(error, model) {
var margin = {top: 20, right: 20, bottom: 50, left: 45};
var width = 900 - margin.left - margin.right;
var height = 500 - margin.top - margin.bottom;
var xPadding = 20;
var yPadding = 35;
var leaves = get_leaves(model.model.root);
var max_support = (leaves.sort(function (x, y) {
return y.count - x.count})[0].count)/model.rows;
var xScale = d3.scale.linear()
.domain([0, max_support + 0.025])
.range([0, width]);
var yScale = d3.scale.linear()
.domain([0, 1])
.range([height, 0]);
var xAxis = d3.svg.axis()
.scale(xScale)
.orient("bottom")
.ticks(15);
var yAxis = d3.svg.axis()
.scale(yScale)
.orient("left")
.ticks(25);
var colorPrediction = d3.scale.category10();
var colorLookup = function(leaf) {
return hoverAdjust(leaf, colorPrediction(leaf.output));
};
// SVG panel.
var svg = d3.select("#chart")
.append("svg")
.attr("width", width + margin.left + margin.right)
.attr("height", height + margin.top + margin.bottom)
.append("g")
.attr("transform", "translate(" + margin.left + "," + margin.top + ")");
// Adds X axis
svg.append("g")
.attr("class", "x axis")
.attr("transform", "translate(0," + height + ")")
.call(xAxis)
.append("text")
.attr("class", "label")
.attr("x", width/2)
.attr("y", 32)
.style("text-anchor", "middle")
.text("Support");
// Adds Y axis
svg.append("g")
.attr("class", "y axis")
.call(yAxis)
.append("text")
.attr("class", "label")
.attr("transform", "rotate(-90)")
.attr("x", -height/2)
.attr("y", -45)
.attr("dy", ".71em")
.style("text-anchor", "middle")
.text("Confidence")
// Draw X-axis grid lines
svg.selectAll("line.x")
.data(xScale.ticks(10))
.enter().append("line")
.attr("class", "x")
.attr("x1", xScale)
.attr("x2", xScale)
.attr("y1", 0)
.attr("y2", height)
.style("stroke", "#ccc");
// Draw Y-axis grid lines
svg.selectAll("line.y")
.data(yScale.ticks(10))
.enter().append("line")
.attr("class", "y")
.attr("x1", 0)
.attr("x2", width)
.attr("y1", yScale)
.attr("y2", yScale)
.style("stroke", "#ccc");
// Output
svg.append('text')
.attr("text-anchor", "middle")
.attr({'id': 'outputLabel', 'x': width/2, 'y': height-20})
.style({'font-size': '40px', 'font-weight': 'bold', 'fill': '#ddd'});
// Draw leaves
svg.selectAll("circle")
.data(leaves)
.enter()
.append("circle")
.attr("cx", function(leaf) {
return xScale(leaf.count/model.rows);
})
.attr("cy", function(leaf) {
return yScale(leaf.confidence);
})
.attr("r", function(leaf) {
return 2 * Math.sqrt(height - yScale(leaf.count/model.rows));
})
.attr("fill", colorLookup)
.attr("stroke", colorLookup)
.style('cursor', 'pointer')
.on('mouseover', function(leaf) {
d3.select('svg #outputLabel')
.text(leaf.output + " (" + ((leaf.count/model.rows) * 100).toFixed(2) + "%, " + (leaf.confidence * 100).toFixed(2) + "%)")
.transition()
.style('opacity', 1);
})
.on('mouseout', function(d) {
d3.select('svg #outputLabel')
.transition()
.duration(1500)
.style('opacity', 0);
});
// Draw legends
var legend = svg.selectAll(".legend")
.data(colorPrediction.domain())
.enter().append("g")
.attr("class", "legend")
.attr("transform", function(d, i) { return "translate(0," + i * 20 + ")"; });
legend.append("rect")
.attr("x", width - 18)
.attr("width", 18)
.attr("height", 18)
.style("fill", colorPrediction);
legend.append("text")
.attr("x", width - 24)
.attr("y", 9)
.attr("dy", ".35em")
.style("text-anchor", "end")
.text(function(d) { return d; });
});
// Returns the list of leaves of a tree
function get_leaves(node) {
var leaves = [];
if ('children' in node) {
for (var i=0; i < node.children.length; i++) {
var childLeaves = get_leaves(node.children[i]);
for (var j=0; j < childLeaves.length; j++) {
leaves.push(childLeaves[j]);
}
}
} else {
var distribution = [];
if ('bins' in node.objective_summary) {
distribution = node.objective_summary.bins;
}
else if ('counts' in node.objective_summary) {
distribution = node.objective_summary.counts;
}
else if ('categories' in node.objective_summary) {
distribution = node.objective_summary.categories
}
leaves = [{
"confidence": node.confidence,
"count": node.count,
"distribution": distribution,
"output": node.output}];
}
return leaves;
};
// Adjust hover
function hoverAdjust(d, color) {
return d.hover ? d3.rgb(color).brighter(0.66) : color;
};
</script>
{"category": 0, "code": 200, "columns": 12, "created": "2013-03-29T05:54:48.938000", "credits": 13.375984191894531, "credits_per_prediction": 0.0, "dataset": "dataset/51552c9e0c0b5e04c2000164", "dataset_status": true, "description": "", "excluded_fields": [], "fields_meta": {"count": 12, "limit": 1000, "offset": 0, "total": 12}, "input_fields": ["000000", "000001", "000002", "000003", "000004", "000005", "000006", "000007", "000008", "000009", "00000a"], "locale": "en-US", "max_columns": 13, "max_rows": 32561, "model": {"depth_threshold": 20, "fields": {"000000": {"column_number": 0, "datatype": "int8", "name": "age", "optype": "numeric", "order": 0, "preferred": true, "summary": {"bins": [[18.75643, 2410], [21.51515, 1485], [23.47642, 1675], [25.48278, 1626], [27.5094, 1702], [29.51434, 1674], [31.48252, 1716], [33.50312, 1761], [35.5062, 1774], [37.4908, 1685], [39.49317, 1610], [41.49118, 1588], [43.48461, 1494], [46.38942, 2722], [50.4325, 2252], [53.47213, 879], [55.46624, 785], [57.50552, 724], [59.46777, 667], [61.46237, 558], [63.47489, 438], [65.45732, 328], [67.4428, 271], [69.45178, 197], [71.48201, 139], [73.44348, 115], [75.50549, 91], [77.44231, 52], [80.28947, 76], [83.95, 20], [87.75, 4], [90, 43]], "maximum": 90, "mean": 38.58165, "median": 37.03324, "minimum": 17, "missing_count": 0, "population": 32561, "splits": [18.58199, 20.00208, 21.38779, 22.6937, 23.89609, 25.137, 26.40151, 27.62339, 28.8206, 30.03925, 31.20051, 32.40167, 33.57212, 34.72468, 35.87617, 37.03324, 38.24651, 39.49294, 40.76573, 42.0444, 43.3639, 44.75256, 46.13703, 47.60107, 49.39145, 51.09725, 53.14627, 55.56526, 58.35547, 61.50785, 66.43583], "standard_deviation": 13.64043, "sum": 1256257, "sum_squares": 54526623, "variance": 186.0614}}, "000001": {"column_number": 1, "datatype": "string", "name": "workclass", "optype": "categorical", "order": 1, "preferred": true, "summary": {"categories": [["Private", 22696], ["Self-emp-not-inc", 2541], ["Local-gov", 2093], ["State-gov", 1298], ["Self-emp-inc", 1116], ["Federal-gov", 960], ["Without-pay", 14], ["Never-worked", 7]], "missing_count": 1836}}, "000002": {"column_number": 2, "datatype": "string", "name": "education", "optype": "categorical", "order": 2, "preferred": true, "summary": {"categories": [["HS-grad", 10501], ["Some-college", 7291], ["Bachelors", 5355], ["Masters", 1723], ["Assoc-voc", 1382], ["11th", 1175], ["Assoc-acdm", 1067], ["10th", 933], ["7th-8th", 646], ["Prof-school", 576], ["9th", 514], ["12th", 433], ["Doctorate", 413], ["5th-6th", 333], ["1st-4th", 168], ["Preschool", 51]], "missing_count": 0}}, "000003": {"column_number": 3, "datatype": "string", "name": "marital-status", "optype": "categorical", "order": 3, "preferred": true, "summary": {"categories": [["Married-civ-spouse", 14976], ["Never-married", 10683], ["Divorced", 4443], ["Separated", 1025], ["Widowed", 993], ["Married-spouse-absent", 418], ["Married-AF-spouse", 23]], "missing_count": 0}}, "000004": {"column_number": 4, "datatype": "string", "name": "occupation", "optype": "categorical", "order": 4, "preferred": true, "summary": {"categories": [["Prof-specialty", 4140], ["Craft-repair", 4099], ["Exec-managerial", 4066], ["Adm-clerical", 3770], ["Sales", 3650], ["Other-service", 3295], ["Machine-op-inspct", 2002], ["Transport-moving", 1597], ["Handlers-cleaners", 1370], ["Farming-fishing", 994], ["Tech-support", 928], ["Protective-serv", 649], ["Priv-house-serv", 149], ["Armed-Forces", 9]], "missing_count": 1843}}, "000005": {"column_number": 5, "datatype": "string", "name": "relationship", "optype": "categorical", "order": 5, "preferred": true, "summary": {"categories": [["Husband", 13193], ["Not-in-family", 8305], ["Own-child", 5068], ["Unmarried", 3446], ["Wife", 1568], ["Other-relative", 981]], "missing_count": 0}}, "000006": {"column_number": 6, "datatype": "string", "name": "race", "optype": "categorical", "order": 6, "preferred": true, "summary": {"categories": [["White", 27816], ["Black", 3124], ["Asian-Pac-Islander", 1039], ["Amer-Indian-Eskimo", 311], ["Other", 271]], "missing_count": 0}}, "000007": {"column_number": 7, "datatype": "string", "name": "sex", "optype": "categorical", "order": 7, "preferred": true, "summary": {"categories": [["Male", 21790], ["Female", 10771]], "missing_count": 0}}, "000008": {"column_number": 8, "datatype": "int32", "name": "capital-gain", "optype": "numeric", "order": 8, "preferred": true, "summary": {"bins": [[0.02291, 29855], [583.27778, 36], [1052.2963, 54], [1603.7037, 54], [2319.77922, 231], [3022.86667, 225], [3412.46763, 139], [3972.7218, 133], [4575.77419, 186], [5109.11976, 167], [5523.57895, 19], [6097, 1], [6459.96429, 28], [6829.52941, 34], [7305.35769, 260], [7691.17361, 288], [8614, 55], [9413.07692, 26], [10541.2459, 61], [11678, 2], [13550, 27], [14184.89552, 67], [15023.94318, 352], [15831, 6], [18481, 2], [20051, 37], [22040, 1], [25206.13333, 15], [27828, 34], [34095, 5], [41310, 2], [99999, 159]], "maximum": 99999, "mean": 1077.64884, "median": 5.30214, "minimum": 0, "missing_count": 0, "population": 32561, "splits": [5.30214], "standard_deviation": 7385.29208, "sum": 35089324, "sum_squares": 1813719045084, "variance": 54542539.17841}}, "000009": {"column_number": 9, "datatype": "int16", "name": "capital-loss", "optype": "numeric", "order": 9, "preferred": true, "summary": {"bins": [[0, 31042], [155, 1], [213, 4], [323, 3], [419, 3], [630.6, 15], [810, 2], [880, 6], [974, 2], [1102.22222, 9], [1258, 4], [1340, 7], [1401.34483, 29], [1490.65714, 70], [1592.57059, 170], [1667.54795, 73], [1736.03125, 128], [1887.39083, 458], [1981.24706, 255], [2050.56757, 37], [2182.56818, 44], [2254.45, 40], [2340.36842, 19], [2411.77083, 96], [2567.19048, 21], [2754, 2], [2824, 10], [3004, 2], [3683, 2], [3770, 2], [3900, 2], [4356, 3]], "maximum": 4356, "mean": 87.30383, "median": 3.83993, "minimum": 0, "missing_count": 0, "population": 32561, "splits": [3.83993], "standard_deviation": 402.96022, "sum": 2842700, "sum_squares": 5535171692, "variance": 162376.93781}}, "00000a": {"column_number": 10, "datatype": "int8", "name": "hours-per-week", "optype": "numeric", "order": 10, "preferred": true, "summary": {"bins": [[1.61538, 52], [4.68664, 217], [7.84795, 171], [9.93919, 296], [12.33195, 241], [15.33662, 609], [17.72115, 104], [20.07504, 1306], [24.72979, 977], [27.74138, 116], [29.99394, 1156], [32.26627, 338], [35.14502, 1517], [37.7616, 625], [40.02811, 15510], [44.80961, 2269], [47.91343, 566], [50.0867, 2999], [55.007, 857], [57.62222, 45], [60.022, 1500], [64.94035, 285], [67.75, 16], [70.40659, 364], [74.98507, 67], [77.29412, 17], [80.0365, 137], [84.22414, 58], [86.33333, 3], [89.97297, 37], [95.8, 10], [98.88542, 96]], "maximum": 99, "mean": 40.43746, "median": 40.06163, "minimum": 1, "missing_count": 0, "population": 32561, "splits": [14.47328, 19.73604, 23.54733, 28.33078, 30.47572, 34.89747, 36.67729, 39.22601, 39.42911, 39.5635, 39.67161, 39.76463, 39.84754, 39.92305, 39.99284, 40.06163, 40.1358, 40.21695, 40.30751, 40.4118, 40.53898, 40.71834, 43.5524, 44.94996, 45.87216, 49.50563, 49.98745, 50.44867, 55.03869, 59.86356, 64.6363], "standard_deviation": 12.34743, "sum": 1316684, "sum_squares": 58207416, "variance": 152.459}}, "00000c": {"column_number": 12, "datatype": "string", "name": "income", "optype": "categorical", "order": 11, "preferred": true, "summary": {"categories": [["<=50K", 24720], [">50K", 7841]], "missing_count": 0}}}, "importance": [["000008", 0.47427], ["000009", 0.18629], ["000004", 0.15274], ["000002", 0.129], ["00000a", 0.02301], ["000000", 0.01437], ["000001", 0.01348], ["000003", 0.00279], ["000005", 0.00237], ["000006", 0.00128], ["000007", 0.0004]], "kind": "stree", "missing_strategy": "last_prediction", "model_fields": {"000000": {"column_number": 0, "datatype": "int8", "name": "age", "optype": "numeric", "order": 0, "preferred": true}, "000001": {"column_number": 1, "datatype": "string", "name": "workclass", "optype": "categorical", "order": 1, "preferred": true}, "000002": {"column_number": 2, "datatype": "string", "name": "education", "optype": "categorical", "order": 2, "preferred": true}, "000003": {"column_number": 3, "datatype": "string", "name": "marital-status", "optype": "categorical", "order": 3, "preferred": true}, "000004": {"column_number": 4, "datatype": "string", "name": "occupation", "optype": "categorical", "order": 4, "preferred": true}, "000005": {"column_number": 5, "datatype": "string", "name": "relationship", "optype": "categorical", "order": 5, "preferred": true}, "000006": {"column_number": 6, "datatype": "string", "name": "race", "optype": "categorical", "order": 6, "preferred": true}, "000007": {"column_number": 7, "datatype": "string", "name": "sex", "optype": "categorical", "order": 7, "preferred": true}, "000008": {"column_number": 8, "datatype": "int32", "name": "capital-gain", "optype": "numeric", "order": 8, "preferred": true}, "000009": {"column_number": 9, "datatype": "int16", "name": "capital-loss", "optype": "numeric", "order": 9, "preferred": true}, "00000a": {"column_number": 10, "datatype": "int8", "name": "hours-per-week", "optype": "numeric", "order": 10, "preferred": true}, "00000c": {"column_number": 12, "datatype": "string", "name": "income", "optype": "categorical", "order": 12, "preferred": true}}, "root": {"children": [{"children": [{"children": [{"children": [{"children": [{"children": [{"confidence": 0.89903, "count": 323, "objective_summary": {"categories": [[">50K", 22], ["<=50K", 301]]}, "output": "<=50K", "predicate": {"field": "000009", "operator": "<=", "value": 2169}}, {"confidence": 0.34237, "count": 2, "objective_summary": {"categories": [[">50K", 2]]}, "output": ">50K", "predicate": {"field": "000009", "operator": ">", "value": 2169}}], "confidence": 0.89247, "count": 325, "objective_summary": {"categories": [[">50K", 24], ["<=50K", 301]]}, "output": "<=50K", "predicate": {"field": "00000a", "operator": ">", "value": 36}}, {"confidence": 0.95724, "count": 86, "objective_summary": {"categories": [["<=50K", 86]]}, "output": "<=50K", "predicate": {"field": "00000a", "operator": "<=", "value": 36}}], "confidence": 0.91458, "count": 411, "objective_summary": {"categories": [[">50K", 24], ["<=50K", 387]]}, "output": "<=50K", "predicate": {"field": "000002", "operator": "=", "value": "Assoc-acdm"}}, {"children": [{"children": [{"children": [{"confidence": 0.60692, "count": 197, "objective_summary": {"categories": [[">50K", 64], ["<=50K", 133]]}, "output": "<=50K", "predicate": {"field": "000003", "operator": "=", "value": "Divorced"}}, {"confidence": 0.58096, "count": 23, "objective_summary": {"categories": [[">50K", 5], ["<=50K", 18]]}, "output": "<=50K", "predicate": {"field": "000003", "operator": "=", "value": "Separated"}}, {"confidence": 0.48049, "count": 15, "objective_summary": {"categories": [[">50K", 4], ["<=50K", 11]]}, "output": "<=50K", "predicate": {"field": "000003", "operator": "=", "value": "Married-spouse-absent"}}, {"children": [{"confidence": 0.43849, "count": 3, "objective_summary": {"categories": [["<=50K", 3]]}, "output": "<=50K", "predicate": {"field": "000004", "operator": "=", "value": "Exec-managerial"}}, {"confidence": 0.31951, "count": 12, "objective_summary": {"categories": [["<=50K", 5], [">50K", 7]]}, "output": ">50K", "predicate": {"field": "000004", "operator": "!=", "value": "Exec-managerial"}}], "confidence": 0.33178, "count": 16, "objective_summary": {"categories": [[">50K", 7], ["<=50K", 9]]}, "output": "<=50K", "predicate": {"field": "000003", "operator": "=", "value": "Widowed"}}, {"confidence": 0.34237, "count": 2, "objective_summary": {"categories": [[">50K", 2]]}, "output": ">50K", "predicate": {"field": "000003", "operator": "=", "value": "Married-AF-spouse"}}, {"confidence": 0.71708, "count": 321, "objective_summary": {"categories": [[">50K", 75], ["<=50K", 246]]}, "output": "<=50K", "predicate": {"field": "000003", "operator": "=", "value": "Never-married"}}], "confidence": 0.6886, "count": 574, "objective_summary": {"categories": [[">50K", 157], ["<=50K", 417]]}, "output": "<=50K", "predicate": {"field": "000009", "operator": "<=", "value": 2351}}, {"confidence": 0.60966, "count": 6, "objective_summary": {"categories": [[">50K", 6]]}, "output": ">50K", "predicate": {"field": "000009", "operator": ">", "value": 2351}}], "confidence": 0.68103, "count": 580, "objective_summary": {"categories": [[">50K", 163], ["<=50K", 417]]}, "output": "<=50K", "predicate": {"field": "00000a", "operator": ">", "value": 42}}, {"children": [{"children": [{"children": [{"confidence": 0.96265, "count": 99, "objective_summary": {"categories": [["<=50K", 99]]}, "output": "<=50K", "predicate": {"field": "00000a", "operator": "<=", "value": 38}}, {"confidence": 0.91884, "count": 314, "objective_summary": {"categories": [[">50K", 16], ["<=50K", 298]]}, "output": "<=50K", "predicate": {"field": "00000a", "operator": ">", "value": 38}}], "confidence": 0.938, "count": 413, "objective_summary": {"categories": [[">50K", 16], ["<=50K", 397]]}, "output": "<=50K", "predicate": {"field": "000004", "operator": "!=", "value": "Prof-specialty"}}, {"confidence": 0.85615, "count": 208, "objective_summary": {"categories": [[">50K", 20], ["<=50K", 188]]}, "output": "<=50K", "predicate": {"field": "000004", "operator": "=", "value": "Prof-specialty"}}], "confidence": 0.92263, "count": 636, "objective_summary": {"categories": [[">50K", 36], ["<=50K", 600]]}, "output": "<=50K", "predicate": {"field": "000000", "operator": "<=", "value": 42}}, {"children": [{"children": [{"confidence": 0.5101, "count": 4, "objective_summary": {"categories": [[">50K", 4]]}, "output": ">50K", "predicate": {"field": "000001", "operator": "=", "value": "Private"}}, {"confidence": 0.20765, "count": 3, "objective_summary": {"categories": [[">50K", 1], ["<=50K", 2]]}, "output": "<=50K", "predicate": {"field": "000001", "operator": "!=", "value": 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