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Unsupervised Learning and Dimensionality Reduction

Complete source code used to reproduce experiments used in writing analysis report of unsupervised and dimensionality reduction algorithms is available at below GitHub repo:

https://github.com/srkrkalyan/unsupervised_learning.git

In order to reproduce either of the clustering or dimensionality reduction or ANN on clustering + dimensionality reduction experiments, please follow below mentioned steps:

  1. Clone or download all source files and data sets from below GitHub repo into one local directory:

https://github.com/srkrkalyan/unsupervised_learning.git

  1. System requirements before running any .py files downloaded in step #1:

    a. Python 3.6.8 b. matplotlib 3.0.2 c. sklearn 0.20.2 d. pandas 0.24.0 e. numpy 1.15.4 f. scipy 1.2.0

  2. Install Python 3.6 environment and other modules listed in step #2

  3. Provided below is the file name and associated experiment:

    Clustering Experiments:

    a. breast_cancer_k_means.py: k-means clustering, print metrics, plot clustering results of Breast Cancer Dataset b. breast_cancer_EM.py: EM clustering, print metrics, plot clustering results of Breast Cancer Dataset c. travel_insurance_k_means.py: k-means clustering, print metrics, plot clustering results of Travel Insurance Dataset d. travel_insurance_EM.py: EM clustering, print metrics, plot clustering results of Travel Insurance Dataset

    Dimensionality Reduction Experiments:

    e. breast_cancer_PCA.py: PCA transformation, runs ANN on PCA transformed dataset, k-means & EM clustering of PCA transformed breast cancer dataset f. breast_cancer_ICA.py: ICA transformation, runs ANN on ICA transformed dataset, k-means & EM clustering of ICA transformed breast cancer dataset g. breast_cancer_Random Projections.py: RP transformation, runs ANN on RP transformed dataset, k-means & EM clustering of RP transformed breast cancer dataset h. breast_cancer_SVD.py: SVD transformation, runs ANN on SVD transformed dataset, k-means & EM clustering of SVD transformed breast cancer dataset i. travel_insurance_PCA.py: PCA transformation, runs ANN on PCA transformed dataset, k-means & EM clustering of PCA transformed dataset, runs ANN on data projected using clustering algorithms for travel insurance dataset j. travel_insurance_ICA.py: ICA transformation, runs ANN on ICA transformed dataset, k-means & EM clustering of ICA transformed dataset, runs ANN on data projected using clustering algorithms for travel insurance dataset k. travel_insurance_Randomized Projections.py: RP transformation, runs ANN on RP transformed dataset, k-means & EM clustering of RP transformed dataset, runs ANN on data projected using clustering algorithms for travel insurance dataset l. travel_insurance_SVD.py: SVD transformation, runs ANN on SVD transformed dataset, k-means & EM clustering of SVD transformed dataset, runs ANN on data projected using clustering algorithms for travel insurance dataset

    Datasets:

    m. breast_cancer.data.csv: Breast cancer dataset used for experiments n. travel_insurance: Travel Insurance dataset used for experiments

    ANN experiments

    o. breast_cancer_ANN.py: ANN run for breast cancer dataset p. travel_insurance_ANN.py: ANN run for travel insurance dataset

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