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+-10.704322649340714,-2.487943510410031,-4.125107588263418,4.156085958594155,2.679252864381553,0.0 +1.314098275763449,6.747289661066285,-5.258672410020185,-11.20524600806105,-5.8069969064331035,1.0 +-9.547278908497052,-2.6782465866091987,-4.561887467990914,3.5280377778614365,0.1265178509797784,0.0 diff --git a/data/diabetes.csv b/data/diabetes.csv index d498636..d9062e7 100755 --- a/data/diabetes.csv +++ b/data/diabetes.csv @@ -1,4 +1,4 @@ -Preg.,Glucose,BloodPres.,SkinThic.,Insulin,BMI,Diab.Pedig.,Age,Outcome* +Pregnancies,Glucose,BloodPress.,SkinThick.,Insulin,BMI,DPF,Age,Outcome* 6,148,72,35,0,33.6,0.627,50,1 1,85,66,29,0,26.6,0.351,31,0 8,183,64,0,0,23.3,0.672,32,1 diff --git a/index.html b/index.html index e7d87ef..0e0e93a 100755 --- a/index.html +++ b/index.html @@ -181,7 +181,7 @@
- Density (1/sigma) + Density +
3 @@ -220,10 +220,10 @@
- +
- +
@@ -270,7 +270,7 @@
-

Dimension Correlation

+

Dimension Correlation

@@ -286,9 +286,14 @@
-

1/sigma and KLD Distributions

+

Density and Remaining Cost Distributions

+
+
+
+ -
+
+
diff --git a/js/tsne_vis.js b/js/tsne_vis.js index 846a1bb..7f07845 100755 --- a/js/tsne_vis.js +++ b/js/tsne_vis.js @@ -1325,7 +1325,7 @@ function CostHistogram(points){ } var trace1 = { x: frequency2, - name: '1/sigma', + name: 'Density', autobinx: false, marker: { color: "rgb(0,128,0)", @@ -1350,7 +1350,7 @@ function CostHistogram(points){ } var trace2 = { x: frequency, - name: 'KLD(P||Q)', + name: 'Remaining Cost', autobinx: false, histnorm: "count", marker: { @@ -1383,7 +1383,7 @@ function CostHistogram(points){ t: 10, pad: 4 }, - xaxis:{range: [0,1.01],title: 'Normalized Bins from Min to Max Values.', + xaxis:{range: [0,1.01],title: 'Normalized bins from min to max values.', titlefont: { size: 14, color: 'black' @@ -1744,7 +1744,7 @@ function CalculateCorrel(flagForSchema){ // Calculate the correlation is a funct if (isNaN(pearsonCorrelation(tempData, 0, 1))) { } else{ SignStore.push([temp, pearsonCorrelation(tempData, 0, 1)]); // Keep the sign - correlationResults.push([Object.keys(dataFeatures[0])[temp] + " (" + temp + ")", Math.abs(pearsonCorrelation(tempData, 0, 1)),temp]); // Find the pearson correlations + correlationResults.push([Object.keys(dataFeatures[0])[temp], Math.abs(pearsonCorrelation(tempData, 0, 1)),temp]); // Find the pearson correlations //correlationResults.push([Object.keys(dataFeatures[0])[temp] + " (" + temp + ")", Math.pow(pearsonCorrelation(tempData, 0, 1),2),temp]); // Find the pearson correlations (MAYBE!) } } @@ -1802,7 +1802,6 @@ function CalculateCorrel(flagForSchema){ // Calculate the correlation is a funct } } } - drawBarChart(); // Draw the horizontal barchart with the correlations. } @@ -2448,7 +2447,7 @@ if (points.length) { // If points exist (at least 1 point) var trace1 = { x: kValuesLegend, y: StoreInitialFindNearestTable, - name: 'Entire Projection', + name: 'Projection average', type: 'bar', marker: { color: 'rgb(0,0,0)' @@ -2457,7 +2456,7 @@ if (points.length) { // If points exist (at least 1 point) var trace2 = { x: kValuesLegend, y: findNearestTable, - name: 'Lasso Selected Cluster', + name: 'Selected points', type: 'bar', marker: { color: 'rgb(0, 187, 187)' @@ -2477,13 +2476,13 @@ if (points.length) { // If points exist (at least 1 point) pad: 4 }, xaxis: {range: [0, LimitXaxis], - title: 'K Values for K-NN', + title: 'Number of neighbors', titlefont: { size: 12, color: 'black' }}, yaxis: { - title: 'Cl. Purity', + title: 'n, %', titlefont: { size: 12, color: 'black' @@ -2746,7 +2745,7 @@ if (points.length) { // If points exist (at least 1 point) .labelFormat(d3.format(",.0f")) .cells(9) .labels([abbr_labels_beta[0],abbr_labels_beta[1],abbr_labels_beta[2],abbr_labels_beta[3],abbr_labels_beta[4],abbr_labels_beta[5],abbr_labels_beta[6],abbr_labels_beta[7],abbr_labels_beta[8]]) - .title("1/sigma") + .title("Density") .scale(colorScale); svg.select(".legendLinear") @@ -2759,19 +2758,18 @@ if (points.length) { // If points exist (at least 1 point) .attr("transform", "translate(10,20)"); var SizeRange1 = []; - SizeRange1.push((minSize1).toFixed(3)); - SizeRange1.push(((maxSize1-minSize1)/2).toFixed(3)); - SizeRange1.push((maxSize1).toFixed(3)); + SizeRange1.push((minSize1).toFixed(4)); + SizeRange1.push(((maxSize1-minSize1)/2).toFixed(4)); + SizeRange1.push((maxSize1).toFixed(4)); var legendSize1 = d3.legendSize() .scale(legendScale1) - .labelFormat(d3.format(",.5f")) .cells(3) .shape('circle') .labels([SizeRange1[0],SizeRange1[1],SizeRange1[2]]) .shapePadding(10) .labelOffset(5) - .title("KLD(P||Q)") + .title("Remaining Cost") .orient('vertical'); svg.select(".legendSize") @@ -2834,7 +2832,7 @@ if (points.length) { // If points exist (at least 1 point) .labelFormat(d3.format(",.5f")) .cells(9) .labels([abbr_labels_cost[0],abbr_labels_cost[1],abbr_labels_cost[2],abbr_labels_cost[3],abbr_labels_cost[4],abbr_labels_cost[5],abbr_labels_cost[6],abbr_labels_cost[7],abbr_labels_cost[8]]) - .title("KLD(P||Q)") + .title("Remaining Cost") .scale(colorScale); svg.select(".legendLinear") @@ -2854,7 +2852,7 @@ if (points.length) { // If points exist (at least 1 point) svg.append("g") .attr("class", "legendSize") - .attr("transform", "translate(15,20)"); + .attr("transform", "translate(45,20)"); var SizeRange2 = []; SizeRange2.push(0); @@ -2870,7 +2868,7 @@ if (points.length) { // If points exist (at least 1 point) .labels([SizeRange2[0],SizeRange2[1],SizeRange2[2]]) .shapePadding(10) .labelOffset(5) - .title("1/sigma") + .title("Density") .orient('vertical'); svg.select(".legendSize") @@ -2977,6 +2975,7 @@ if (points.length) { // If points exist (at least 1 point) var color = new THREE.Color("rgb(145, 145, 145)"); } else if (ColSizeSelector == "color") { var color = new THREE.Color(colorScale(points[i].beta)); + //var color = new THREE.Color("rgb(125, 125, 125)"); } else{ if (points[i].cost < min){ @@ -3062,7 +3061,7 @@ if (points.length) { // If points exist (at least 1 point) .labelFormat(d3.format(",.0f")) .cells(9) .labels([abbr_labels_beta[0],abbr_labels_beta[1],abbr_labels_beta[2],abbr_labels_beta[3],abbr_labels_beta[4],abbr_labels_beta[5],abbr_labels_beta[6],abbr_labels_beta[7],abbr_labels_beta[8]]) - .title("1/sigma") + .title("Density") .scale(colorScale); svg.select(".legendLinear") @@ -3114,7 +3113,7 @@ if (points.length) { // If points exist (at least 1 point) .labelFormat(d3.format(",.5f")) .cells(7) .labels([abbr_labels_cost[0],abbr_labels_cost[1],abbr_labels_cost[2],abbr_labels_cost[3],abbr_labels_cost[4],abbr_labels_cost[5],abbr_labels_cost[6]]) - .title("KLD(P||Q)") + .title("Remaining Cost") .scale(colorScale); svg.select(".legendLinear")