A 2D partial dependency plot of a random decision forest trained to predict forest cover.
- Click and drag to zoom in.
- Double click to zoom out.
A 2D partial dependency plot of a random decision forest trained to predict forest cover.
A partial dependence plot of a BigML random decision forest built on the iris dataset.
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An association graph of correlated values found with BigML's association rules (in collaboration with Geoff Webb) on the UCI mushroom dataset.
Move the slider to increase or decrease the number of rules used to build the graph. The highest quality rules (as defined by leverage) are included first. As the number of rules increase, the "min leverage" will drop indicating that weaker associations are being
A visualization of a test dataset with some negative valued outliers. The distribution is stored with a streaming histogram.
t
to toggle trimming some of the outliers from the distribution.r
to toggle rounding populations for each bin.i
to toggle the distribution interpolation mode.A visualization of wine densities using distributions from two separate clusters (kmeans). The distributions are stored with a streaming histogram.
t
to toggle trimming some of the outliers from the distribution.r
to toggle rounding populations for each bin.i
to toggle the distribution interpolation mode.A visualization of sulphates in wine using distributions from two separate clusters (kmeans). The distributions are stored with a streaming histogram.
t
to toggle trimming some of the outliers from the distribution.r
to toggle rounding populations for each bin.i
to toggle the distribution interpolation mode.A visualization of blood plasma from the UCI diabetes dataset. The distribution is stored with a streaming histogram.
t
to toggle trimming some of the outliers from the distribution.r
to toggle rounding populations for each bin.i
to toggle the distribution interpolation mode.Dynamic scatterplot of the 1985 automobiles dataset.
Controls:
Dynamic scatterplot of the a sample from the wine quality dataset, including four clusters found with BigML's kmeans.
Controls: