https://github.com/taneeshkareddy/ml-lab-practise

https://github.com/taneeshkareddy/ml-lab-practise

Last synced: about 2 months ago
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• Host: GitHub
• URL: https://github.com/taneeshkareddy/ml-lab-practise
• Owner: TaneeshkaReddy
• Created: 2024-07-23T04:06:16.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-07-23T04:08:26.000Z (5 months ago)
• Last Synced: 2024-08-14T09:25:55.796Z (5 months ago)
• Language: Jupyter Notebook
• Size: 420 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
ML Lab

Programs for Machine Learning Lab internals (20CS67L)

1 Visualize the n-dimensional data using 3D surface plots. Write a program to implement the Best First Search (BFS) algorithm.

2 Visualize the n-dimensional data using contour plots. Write a program to implement the A* algorithm

3 Visualize the n-dimensional data using heat-map. Write a program to implement Min-Max algorithm.

4 Visualize the n-dimensional data using Box-plot. Write a program to implement Alpha-beta pruning algorithm.

5 Write a program to develop the Naive Bayes classifier on Titanic dataset.

6 Write a program to develop the KNN classifier with Euclidean distance and Manhattan distance for the k values as 3 based on split up of training and testing dataset as 70-30 on Glass dataset.

7 Write a program to develop a decision tree classifier based on weather forecasting dataset.

8 Write a program to perform unsupervised K-means clustering techniques on Iris dataset.

9 Write a program to perform agglomerative clustering based on single-linkage, complete-linkage criteria.

10 Write a program to develop a decision tree classifier based on weather forecasting dataset.

11 Write a program to develop Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) algorithms.