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Pima Indians Diabetes - Scattergraph (support vs confidence)
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| <!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> | |
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| {"category": 0, "code": 200, "columns": 9, "created": "2013-03-29T05:46:08.980000", "credits": 0.09991073608398438, "credits_per_prediction": 0.0, "dataset": "dataset/515376ce035d0731c3000106", "dataset_status": true, "description": "", "excluded_fields": [], "fields_meta": {"count": 9, "limit": 1000, "offset": 0, "total": 9}, "input_fields": ["000000", "000001", "000002", "000003", "000004", "000005", "000006", "000007"], "locale": "en-US", "max_columns": 9, "max_rows": 768, "model": {"depth_threshold": 20, "fields": {"000000": {"column_number": 0, "datatype": "int8", "name": "pregnancies", "optype": "numeric", "order": 0, "preferred": true, "summary": {"counts": [[0, 111], [1, 135], [2, 103], [3, 75], [4, 68], [5, 57], [6, 50], [7, 45], [8, 38], [9, 28], [10, 24], [11, 11], [12, 9], [13, 10], [14, 2], [15, 1], [17, 1]], "maximum": 17, "mean": 3.84505, "median": 2.96687, "minimum": 0, "missing_count": 0, "population": 768, "standard_deviation": 3.36958, "sum": 2953, "sum_squares": 20063, "variance": 11.35406}}, "000001": {"column_number": 1, "datatype": "int16", "name": "plasma_glucose", "optype": "numeric", "order": 1, "preferred": true, "summary": {"bins": [[0, 5], [44, 1], [56.66667, 3], [61.5, 2], [67.2, 5], [73.3125, 16], [79.79167, 24], [84.26923, 26], [89.64706, 51], [95.29787, 47], [100.97183, 71], [107.21739, 69], [111.48148, 27], [114.57576, 33], [118.5641, 39], [123.68852, 61], [128.62162, 37], [132.57143, 21], [137.52632, 38], [142.65217, 23], [146.4, 25], [150.92857, 14], [154.5625, 16], [158.15385, 13], [162.4, 15], [166.5, 14], [172, 15], [176.16667, 6], [180.125, 16], [183.5, 6], [188.23077, 13], [195.6875, 16]], "maximum": 199, "mean": 120.89453, "median": 116.86008, "minimum": 0, "missing_count": 0, "population": 768, "splits": [73.4641, 80.66667, 84.54447, 88.29199, 91.05556, 94.06937, 96.48528, 99.20588, 100.75, 102.94511, 105.49074, 107.39491, 109.36701, 111.65834, 114.22967, 116.86008, 119.5, 122.08422, 124.38851, 126.57295, 129.07275, 132.7, 136.75, 140.5, 144.71612, 148.66667, 154.90098, 161.82574, 168.66667, 179.1, 187.58579], "standard_deviation": 31.97262, "sum": 92847, "sum_squares": 12008759, "variance": 1022.24831}}, "000002": {"column_number": 2, "datatype": "int8", "name": "blood pressure", "optype": "numeric", "order": 2, "preferred": true, "summary": {"bins": [[0, 35], [24, 1], [30, 2], [39, 2], [44.66667, 6], [49.44444, 18], [52, 11], [55.04, 25], [58, 21], [60.95833, 72], [64.8375, 80], [68, 45], [70, 57], [72, 44], [74.86869, 99], [78, 45], [80, 40], [82, 30], [84.96, 50], [88, 25], [90, 22], [92, 8], [94.81818, 11], [98, 3], [100, 3], [102, 1], [104, 2], [106, 3], [108, 2], [110, 3], [114, 1], [122, 1]], "maximum": 122, "mean": 69.10547, "median": 71.43285, "minimum": 0, "missing_count": 0, "population": 768, "splits": [4.95379, 47.79361, 52.45455, 56.31476, 58.78684, 60.12982, 61.72909, 62.88889, 64.03541, 65.06458, 66.38178, 67.65685, 68.70061, 69.62414, 70.48722, 71.43285, 72.48913, 73.49, 74.23488, 75.36578, 76.27906, 77.43376, 78.51858, 79.65375, 80.9007, 82.4098, 84.16186, 85.97598, 88.04005, 90.09226, 94.7101], "standard_deviation": 19.35581, "sum": 53073, "sum_squares": 3954989, "variance": 374.64727}}, "000003": {"column_number": 3, "datatype": "int8", "name": "triceps skin thickness", "optype": "numeric", "order": 3, "preferred": true, "summary": {"bins": [[0, 227], [7.5, 4], [10.54545, 11], [12.61111, 18], [14.7, 20], [16.7, 20], [18.47368, 38], [20.43478, 23], [22.57895, 38], [24.57143, 28], [26.58974, 39], [28.45946, 37], [30.41304, 46], [32.39216, 51], [34.65217, 23], [36.53333, 30], [38.72, 25], [40.48387, 31], [42.35294, 17], [44.54545, 11], [46, 8], [47, 4], [48, 4], [49, 3], [50, 3], [51, 1], [52, 2], [54, 2], [56, 1], [60, 1], [63, 1], [99, 1]], "maximum": 99, "mean": 20.53646, "median": 22.81344, "minimum": 0, "missing_count": 0, "population": 768, "splits": [0.46227, 13.14087, 22.81344, 29.82784, 36.68115], "standard_deviation": 15.95222, "sum": 15772, 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"name": "diabetes pedigree", "optype": "numeric", "order": 6, "preferred": true, "summary": {"bins": [[0.09307, 14], [0.14539, 70], [0.19699, 75], [0.25099, 107], [0.29244, 52], [0.34636, 77], [0.41082, 50], [0.45431, 29], [0.50029, 31], [0.54705, 38], [0.59542, 31], [0.64585, 26], [0.6897, 30], [0.74482, 33], [0.82242, 19], [0.87929, 17], [0.94765, 17], [1.015, 5], [1.08729, 7], [1.14571, 7], [1.20238, 8], [1.2702, 5], [1.33067, 3], [1.39375, 4], [1.45933, 3], [1.6, 1], [1.70933, 3], [1.781, 1], [1.893, 1], [2.137, 1], [2.3085, 2], [2.42, 1]], "maximum": 2.42, "mean": 0.47188, "median": 0.3725, "minimum": 0.078, "missing_count": 0, "population": 768, "splits": [0.1275, 0.1445, 0.16159, 0.18, 0.197, 0.209, 0.23241, 0.24341, 0.25471, 0.2609, 0.27067, 0.29, 0.30454, 0.32859, 0.3455, 0.3725, 0.39941, 0.42218, 0.45137, 0.4875, 0.52089, 0.551, 0.58645, 0.6265, 0.669, 0.7005, 0.7425, 0.823, 0.8985, 1.028, 1.2545], "standard_deviation": 0.33133, "sum": 362.401, "sum_squares": 255.20866, 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true}, "000004": {"column_number": 4, "datatype": "int16", "name": "insulin", "optype": "numeric", "order": 4, "preferred": true}, "000005": {"column_number": 5, "datatype": "double", "name": "bmi", "optype": "numeric", "order": 5, "preferred": true}, "000006": {"column_number": 6, "datatype": "double", "name": "diabetes pedigree", "optype": "numeric", "order": 6, "preferred": true}, "000007": {"column_number": 7, "datatype": "int8", "name": "age", "optype": "numeric", "order": 7, "preferred": true}, "000008": {"column_number": 8, "datatype": "string", "name": "diabetes", "optype": "categorical", "order": 8, "preferred": true}}, "root": {"children": [{"children": [{"children": [{"children": [{"confidence": 0.90819, "count": 38, "objective_summary": {"categories": [["false", 38]]}, "output": "false", "predicate": {"field": "000005", "operator": ">", "value": 19.45}}, {"children": [{"confidence": 0.34237, "count": 2, "objective_summary": {"categories": [["true", 2]]}, "output": "true", 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