GitHub topics: sklearn-decomposition

Repositories

sorna-fast/customer_personality_clustering

Customer behavior analysis, data analysis, data frame analysis, and clustering using machine learning

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Aliakbar-omidi/Iris-practice-project

This project is a test modeling for the Iris flower dataset

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tracyreuter/dimensionality-reduction

Increase processing efficiency via principal components analysis

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agustinmassa/reduccion-dimensionalidad

Aplico reducción de dimensionalidad a dos datasets AnsurMen.csv y AnsurWomen.csv

Language: Python - Size: 966 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

swagatika15/FACE-CLASSIFICATION

The aim of this project is to classify the faces. Olivetti Faces dataset has been used. In this dataset there are ten different images of each of 40 distinct subjects. For some subjects, the images were taken at different times, varying the lighting, facial expressions (open / closed eyes, smiling / not smiling) and facial details (glasses / no glasses). All the images were taken against a dark homogeneous background with the subjects in an upright, frontal position (with tolerance for some side movement). The “target” for this database is an integer from 0 to 39 indicating the identity of the person pictured. Each of the sample images needs to be classified in the classes ranging from 0 to 39. PCA has been applied to reduce the dimensionality. Then various classification and regression techniques are used with and without using PCA and the accuracy and time taken by the algorithms are recorded. Algorithms used: SVM, KNN, logistic regression, neural networks, linear regression and random forests.

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