JdMS

Edit Friday, June 14th 2019

Our files:

DataCleaning.ipynb: creating the cleaned dataset, quality assurance, and modifying the data frame. Export the clean data as:

TDataVisualization.ipynb: creating graphs to show relationships/trends not related to the model. Uses the transaction table.
CDataVisualization.ipynb: creating graphs to show relationships/trends not related to the model. Uses the customer table.
Kmeans.ipynb: this is the segmentation model that utilizes k-means to find our clusters.
MeanShift.ipynb: this is the segmentation model that utilizes mean shift to find our clusters.
DBSCAN.ipynb: this is the segmentation model that utilizes DBSCAN to find our clusters.
GowerDistance.ipynb: this is the file that calculates gower's distance for the customer table.
MeanShift.ipynb: this is the model running with the mean shift algorithm.
PCA.ipynb: runs the cleaned customer table through Principal component analysis, reduces the dimensions of the data so it can run smoother.
UMAPS.ipynb: runs the data through UMAPS.

Over the course of the project we will add notes about the files of the project and what we are doing.

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Name		Name	Last commit message	Last commit date
Latest commit History 100 Commits
CDataVisualization.ipynb		CDataVisualization.ipynb
DBSCAN.ipynb		DBSCAN.ipynb
DataCleaning.ipynb		DataCleaning.ipynb
GowerDistance.ipynb		GowerDistance.ipynb
HDBSCAN.ipynb		HDBSCAN.ipynb
Hierarchical.ipynb		Hierarchical.ipynb
KModes-running with PCA.ipynb		KModes-running with PCA.ipynb
KModes.ipynb		KModes.ipynb
Kmeans.ipynb		Kmeans.ipynb
MeanShift.ipynb		MeanShift.ipynb
PCA.ipynb		PCA.ipynb
README.md		README.md
TDataVisualization.ipynb		TDataVisualization.ipynb