Skip to content

Ayantika22/Linear-discriminant-Analysis-LDA-for-Wine-Dataset

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Linear-discriminant-Analysis-LDA-for-Wine-Dataset

Linear discriminant Analysis(LDA) for Wine Dataset of Machine Learning

Requirements

  1. import numpy as np

  2. import pandas as pd

  3. import matplotlib.pyplot as plt

  4. sklearn

  5. Wine dataset

This Program is About Linear Discriminant analysis of Wine dataset.

I have used Jupyter console.

Along with Clustering Visualization Accuracy using Classifiers Such as Logistic regression, KNN, Support vector Machine, Gaussian Naive Bayes, Decision tree and Random forest Classifier is provided. To know the exactness in Accuracy Cohen Kappa is used.

For more information, Cite this paper if referred.

http://www.ijitee.org/wp-content/uploads/papers/v9i7/G5943059720.pdf

https://www.researchgate.net/profile/Ayantika_Nath2/publication/341671505_Clustering_Visualization_and_Class_Prediction_using_Flask_of_Benchmark_Dataset_for_Unsupervised_Techniques_in_ML/links/5ece482292851c9c5e5f8695/Clustering-Visualization-and-Class-Prediction-using-Flask-of-Benchmark-Dataset-for-Unsupervised-Techniques-in-ML.pdf

https://www.researchgate.net/profile/Ayantika_Nath2/publication/341150281_Clustering_Using_Dimensional_Reduction_Techniques_for_Energy_Efficiency_in_WSNs_A_Review/links/5eb10592299bf18b9595b113/Clustering-Using-Dimensional-Reduction-Techniques-for-Energy-Efficiency-in-WSNs-A-Review.pdf

Citing the paper(if referred) is mandatory since the paper has copyrights.

Enjoy Coding

LDA Cluster

alt text