<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. There is also an option to choose between grid parameter search and single set mode.">Parameters</h2>
<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>
<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>
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<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>
<tdstyle="padding-top: 0.8vh !important"><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.">
<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"></i>Execute new t-SNE analysis</button></td>
<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. You can also find the best projections based on a lasso selection of points (with optimize selection).">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"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: in this panel the user can adapt the visual encodings of the main visualization view. Furthermore, the dimension correlation capturing points thresholds are situated in this panel. For the main view, there is also an annotation functionality available.">Visual Mapping</h2>
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<divclass="panel-body"id="commBtn">
<tableclass="table table-borderless">
<tbody>
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<tdscope="row"><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"data-toggle="tooltip"data-placement="right"title="Tip: change between size/radius and color encodings.">Size</label>
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<tr>
<tdscope="row"><labelfor="male"data-toggle="tooltip"data-placement="right"title="Tip: adapt the selection of points in the two-dimensional space. The options are a simple distance measurement between point and line or using the KNN algorithm.">Correl.</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.">Correl. threshold (%)</label>
<tdscope="row"><labelfor="param-lim"data-toggle="tooltip"data-placement="right"title="Tip: x*times the actual radius (increases/decreases points' radius).">Point radius scaling</label></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 target label set a * mark after the appropriate dimension.">Overview</h2><divid="datasetDetails"title="Tip: the number of dimensions/features and instances of a data set."style="display:inline-block; float:right"></div>
<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 (M)</h2>
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<divclass="panel-body"id="resetAllFilters">
<tableclass="table table-borderless centerTable">
<tbody>
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<tdscope="row"><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>Points exploration</button></td>
<td><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></td>
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<tr>
<tdscope="row"><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 correl.</button></td>
<td><buttonclass="btn btn-info"onclick="setReset();"><iclass="fas fa-trash-alt fa-lg"data-toggle="tooltip"data-placement="right"title="Tip: reset all filters applied in the visualizations without losing the execution."></i>Reset all filters</button></td>
<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. If the points/values belong to the diagonal, then the distances are preserved in both spaces. If values are closer to N-D distances, then the visualization is too compressed. If values are closer to 2-D distances, then the visualization is too spread out.">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:-2.2vh; 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 Correlation: #<outputfor="param-corlim"id="param-corlim-value"title="Tip: minimum visible correlation (range: 0.0 to 1.0)."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: the density and remaining cost distributions are important to look at along with the main visualization view individual values.">Density and Remaining Cost</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 Cost: #<outputfor="param-costlim"id="param-costlim-value"title="Tip: minimum visible cost rate (range: 0.1 to 1.0)."style="display:inline-block; float:right">1.0</output></label>
<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). It also works with local selections of points!">Adaptive Parallel Coordinates Plot</h2>
