Input: n-dimensional dataset (ex: numpy array of floats) + covering dimension = k ( any integer between 1 and n)
Output: k-dimensional simplicial complex (k <= n )
Visualization: 2-skeleton of k-dimensional simplicial complex
- numpy
- pandas
- sklearn.decomposition.PCA
- sklearn.cluster.DBSCAN
- json
- d3.js
Data: http://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_iris.html
2-nerve of Iris Dataset
Click here for interactive version.
Data: http://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_breast_cancer.html
2-nerve of Breast Cancer Dataset
Click here for interactive version
Data: http://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_diabetes.html
2-nerve of Diabetes data
Click here for interactive version.
3-nerve of Diabetes data
Click here for interactive version.
Data: https://archive.ics.uci.edu/ml/datasets/Wine+Quality
2-nerve of redwine data
Click here for interactive version.