<h2class="panel-title"style="display:inline-block"data-toggle="tooltip"data-placement="right"title="Tip: control t-SNE algorithm and its parameters.">t-SNE Parameters</h2>
<h2class="panel-title"style="display:inline-block"data-toggle="tooltip"data-placement="right"title="Tip: a panel for controlling the t-SNE algorithm and its parameters.">Parameters</h2>
[Mode:
<selectid="param-EX-view"name="param-EX-view"data-toggle="tooltip"data-placement="right"title="Tip: change between grid search and a single set of parameters."onchange="ExecuteMode()">
<selectid="param-EX-view"name="param-EX-view"data-toggle="tooltip"data-placement="right"title="Tip: the option of changing between grid search (generating 500 projections) and a single set of parameters (1 projection)."onchange="ExecuteMode()">
<divid="cost"title="Tip: the overall cost reduced by each iteration step of the t-SNE algorithm."style="display:inline-block; margin-top:3px; float:right"></div>
</div>
<divclass="panel-body">
<divid="control-panel"data-sr="enter left over 8s">
<divclass="param">
<labelid="data"for="param-dataset"data-toggle="tooltip"data-placement="right"title="Tip: use one of the data sets already provided or upload a new file.">Data sets</label>
<buttontype="button"class="button"id="FactRes"onclick="FactoryReset()"data-toggle="tooltip"data-placement="right"title="Tip: Restart the entire web page/application.">Factory reset</button>
</div>
<divclass="param">
<labelfor="param-perplexity"data-toggle="tooltip"data-placement="right"title="Tip: perplexity is a measure for information that is defined as 2 to the power of the Shannon entropy. The perplexity of a fair die with k sides is equal to k. In t-SNE, the perplexity may be viewed as a knob that sets the number of effective nearest neighbors. (Source: https://lvdmaaten.github.io/tsne/)">Perplexity</label>
<labelfor="param-learningrate"data-toggle="tooltip"data-placement="right"title="Tip: if the learning rate is too high, the data may look like a ‘ball’ with any point approximately equidistant from its nearest neighbours. If the learning rate is too low, most points may look compressed in a dense cloud with few outliers. If the cost function gets stuck in a bad local minimum increasing the learning rate may help. (Source: https://scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html)">Learning rate</label>
<labelfor="param-maxiter"style="padding: 25px 0 0 8px"data-toggle="tooltip"data-placement="right"title="Tip: maximum number of iterations for the optimization. Should usually be around 250. (Source: https://scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html)">Max iterations</label>
</div>
<divclass="col-md-4"style="padding: 25px 0 0 0px">
<outputfor="param-maxiter"id="param-maxiter-value"style="padding: 25px 0 0 0">500</output>
</div>
<divclass="col-md-4">
<divid="hider2"></div>
<tableclass="table table-borderless">
<tbody>
<tr>
<tdscope="row"><labelid="data"for="param-dataset"data-toggle="tooltip"data-placement="right"title="Tip: use one of the data sets already provided (only numerical values supported) or upload a new file (do not forget to use * for the target label).">Data sets</label></td>
<td><buttontype="button"class="button"id="FactRes"onclick="FactoryReset()"data-toggle="tooltip"data-placement="right"title="Tip: Restart the entire web page/application.">Factory reset</button></td>
</tr>
<tr>
<tdscope="row"><labelfor="param-perplexity"data-toggle="tooltip"data-placement="right"title="Tip: perplexity is a measure for information that is defined as 2 to the power of the Shannon entropy. The perplexity of a fair die with k sides is equal to k. In t-SNE, the perplexity may be viewed as a knob that sets the number of effective nearest neighbors. (Source: https://lvdmaaten.github.io/tsne/).">Perplexity</label></td>
<tdscope="row"><labelfor="param-learningrate"data-toggle="tooltip"data-placement="right"title="Tip: if the learning rate is too high, the data may look like a ‘ball’ with any point approximately equidistant from its nearest neighbours. If the learning rate is too low, most points may look compressed in a dense cloud with few outliers. If the cost function gets stuck in a bad local minimum increasing the learning rate may help. (Source: https://scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html).">Learning rate</label></td>
<tdscope="row"><labelfor="param-maxiter"data-toggle="tooltip"data-placement="right"title="Tip: maximum number of iterations for the optimization. Should usually be around 250. (Source: https://scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html).">Max iterations</label></td>
<labeldata-toggle="tooltip"data-placement="right"title="Tip: if you store distances the file size will be larger but on a loading of this execution it will be processed much quicker than without this option enabled.">
<buttontype="button"class="button"onclick='loadAnalysis();'data-toggle="tooltip"data-placement="right"title="Tip: load previously executed analysis in .txt format.">Load execution</button>
</td>
<td><labeldata-toggle="tooltip"data-placement="right"title="Tip: if you store distances the file size will be larger but on a loading of this execution it will be processed much quicker than without this option enabled.">
<inputid="downloadDists"checkedtype="checkbox">
Cache distances
</label>
</div>
</div>
<divclass="row">
<divclass="col-md-12"style="margin-top:10px">
<p><divid="run-button"><buttonid="ExecuteBut"class="btn btn-primary btn-block"onclick="getData();"value="Execute new t-SNE analysis"style="margin-top: 4px"><iclass="fas fa-running fa-lg"style="margin-right: 10px"></i>Execute new t-SNE analysis</button></div></p>
</div>
</div>
</div>
</td>
<td>
<buttontype="button"class="button"onclick="SaveAnalysis()"data-toggle="tooltip"data-placement="right"title="Tip: save/store previously executed analysis in .txt format.">Store execution</button>
</td>
</tr>
<tr>
<tdscope="row"colspan="3"><buttonid="ExecuteBut"class="btn btn-primary btn-block"onclick="getData();"title="Tip: initialize a new t-SNE investigation or start a previous analysis, in case load execution is activated."value="Execute new t-SNE analysis"><iclass="fas fa-running fa-lg"style="margin-right: 10px"></i>Execute new t-SNE analysis</button></td>
<h2class="panel-title"style="display:inline-block"data-toggle="tooltip"data-placement="right"title="Tip: t-SNE overview with or without labels depending on each data set. To determine the feature of a data set that corresponds to classes set a * mark after this feature.">t-SNE Overview</h2><divid="datasetDetails"style="display:inline-block; float:right"></div>
<h2class="panel-title"style="display:inline-block"data-toggle="tooltip"data-placement="right"title="Tip: t-SNE overview with or without labels depending on each data set. To determine the feature of a data set that corresponds to classes set a * mark after this feature.">Overview</h2><divid="datasetDetails"style="display:inline-block; float:right"></div>
@ -3469,7 +3483,7 @@ function OverviewtSNE(points){ // The overview t-SNE function
}
}
}
$("#datasetDetails").html("(Number of Dimensions: "+(Object.keys(dataFeatures[0]).length-valCategExists)+", Number of Instances: "+final_dataset.length+")");// Print on the screen the number of features and instances of the data set, which is being analyzed.
$("#datasetDetails").html("(Num. of Dim.: "+(Object.keys(dataFeatures[0]).length-valCategExists)+", Num. of Ins.: "+final_dataset.length+")");// Print on the screen the number of features and instances of the data set, which is being analyzed.
if(Category==undefined){
$("#CategoryName").html("Classification label: No category");// Print on the screen the classification label.
}else{
@ -3675,7 +3689,7 @@ function CostHistogram(points){
