<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>
[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()">
<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>
<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>
<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.">
<h2class="panel-title"style="display:inline-block"data-toggle="tooltip"data-placement="right"title="Tip: a feature of this tool that supports clusters (and points) exploration. Checking the neighborhood preservation between the entire projection's average and a selection driven by the user.">Projections Provenance</h2>
<buttontype="button"class="buttonOptimize"onclick='OptimizePoints();'style="padding: 5px 5px 5px 5px"data-toggle="tooltip"data-placement="right"title="Tip: find the best projections for the selected points">Optimize Selection</button>
<h2class="panel-title"data-toggle="tooltip"data-placement="right"title="Tip: various functionalities depending on the user. These modes enable different interactions in the main visualization view.">Interaction Modes</h2>
<buttonclass="btn btn-info active"onclick="setLayerProj();"style="margin-left: -1px !important"><iclass="fas fa-mouse-pointer fa-lg"data-toggle="tooltip"data-placement="right"title="Tip: in this mode the user can zoom in and out in the main visualization view and when hovering on a particular point he/she receives the exact data set's instance dimensions."></i>t-SNE Points Exploration</button>
<buttonclass="btn btn-info"onclick="setLayerComp();"style="margin-left: -1.4px"><iclass="far fa-object-group fa-lg"data-toggle="tooltip"data-placement="right"title="Tip: lasso selection in the main visualization view."></i>Group Selection</button>
<buttonclass="btn btn-info"onclick="setLayerSche();"style="margin-left: -2px !important"><iclass="fas fa-draw-polygon fa-lg"data-toggle="tooltip"data-placement="right"title="Tip: draw a shape (polylines) and check the related dimensions correlations for your drawing/shape. With the left click you set one point and the right click you confirm the drawing for further analysis."></i>Dimension Correlation</button>
<buttonclass="btn btn-info"onclick="setReset();"style="margin-left: 225px"><iclass="fas fa-trash-alt fa-lg"style="margin-right: 10px"data-toggle="tooltip"data-placement="right"title="Tip: reset all filters applied in the visualizations without losing the execution."></i>Reset Filters</button>
<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"data-toggle="tooltip"data-placement="right"title="Tip: in this panel the user can adapt the visual mappings of the main visualization view.">Visual Mapping</h2>
<labelfor="male"data-toggle="tooltip"data-placement="right"title="Tip: density in the high-dimensional space taken from the t-SNE itself.">Density</label>
<labelfor="male"data-toggle="tooltip"data-placement="right"title="Tip: remaining cost of each point throughout the entire projection.">Remaining cost</label>
<labelid="selectionLabel"style="margin-top:4px; margin-left: 15px"data-toggle="tooltip"data-placement="right"title="Tip: change between size/radius and color encodings.">Size-encoding</label>
<divclass="param"style="padding: 20px 0 5px 0; margin-top: 5px;">
<labelfor="male"data-toggle="tooltip"data-placement="right"title="Tip: adapt the selection of points in the two-dimensional space: from a simple distance measurement between point and line to KNN algorithm, and vice versa.">Correlation measurement</label>
<labelfor="param-corr"id="param-corrLabel"data-toggle="tooltip"data-placement="right"title="Tip: percentage of all points taken into account by Dimension Correlation.">Correlation threshold (%)</label>
<labelfor="param-lim"data-toggle="tooltip"data-placement="right"title="Tip: x*times the actual radius (increase/decrease points radius).">Points radius scaling</label>
<h2class="panel-title"data-toggle="tooltip"data-placement="right"style="display:inline-block"title="Tip: a view related to the overall quality of the projection.">Shepard Heatmap</h2>
<h2class="panel-title"style="display:inline-block"data-toggle="tooltip"data-placement="right"title="Tip: user-driven shape investigation of the most correlated dimensions.">Dimension Correlation</h2><divclass="param"style="display:inline-block; margin-top:-5px; float:right"><labelfor="param-corlim"style="display:inline-block; float: right"data-toggle="tooltip"data-placement="right"title="Tip: the minimum acceptable visible correlation. Default is 0, so the tool accepts all the correlations.">Min. Visible Correlation: #<outputfor="param-corlim"id="param-corlim-value"style="display:inline-block; float:right">0.0</output></label>
<h2class="panel-title"style="display:inline-block;"data-toggle="tooltip"data-placement="right"title="Tip: it might be useful to take a look at this histogram, to observe the density and remaining cost distributions, when remaining cost values are low and have an idea about the distributions.">Density and Remaining Cost Distributions</h2>
<labelfor="param-costlim"style="display:inline-block; float: right"data-toggle="tooltip"data-placement="right"title="Tip: set the rate of the limiter for the minimum acceptable visible cost at the main visualization view.">Min. Visible Cost Rate: #<outputfor="param-costlim"id="param-costlim-value"style="display:inline-block; float:right">1</output></label>
<h2class="panel-title"style="display:inline-block"data-toggle="tooltip"data-placement="right"title="Tip: a feature of this tool that supports clusters (and points) exploration. Checking the neighborhood preservation between the entire projection's average and a selection driven by the user.">Neighborhood Preservation </h2>
<h2class="panel-title"data-toggle="tooltip"data-placement="right"title="Tip: for every selection the tool runs a local Principal Component Analysis (PCA) algorithm and dynamically adapts and shows the top 8 dimensions in an order from left to right. This sorting from left to right presents the most related (with high variance) features of the data set to the least important (low variance).">Adaptive Parallel Coordinates Plot</h2>