Test Running Regression, Correlation and Clustering

[BradKML]

Correlations:

Trying to Find Beta Coefficients and their related p-values (other than pure Pearson/Spearman Correlation)
Other than that and the display of Column A to Column B correlation, this checks out.

Clustering:

It is hard to view/use the data from a Cluster or a PCA without prior knowledge (i.e. lack of hints)
If there is a way to see the distribution of each cluster, or the cross-correlations of each item within a factor, that would be great.
Also: More Algorithms that are suited to skew and twisted data ala https://scikit-learn.org/stable/auto_examples/cluster/plot_cluster_comparison.html#sphx-glr-auto-examples-cluster-plot-cluster-comparison-py

Machine Learning Models:

It is not known how columns can be specified as either input or output

Naming Scheme of Tabs

"Model" vs "Unsupervised"
Should be Instead "Supervised", "Unsupervised" OR "Model", "Clustering" (and "Distribution")
One should be based on Input vs Output, the other based on Clustering and Dimensionality Reduction (or generalization with no pre-defined output).