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Orion Stark bb6f6deaa4 Glass classification done 6 years ago
datasets/Glass Dataset Init Commit 6 years ago
glass-classification Glass classification done 6 years ago
image-classification Init Commit 6 years ago
iris-classification Init Commit 6 years ago
utils Init Commit 6 years ago
LICENSE Initial commit 6 years ago
README.md Init Commit 6 years ago

README.md

Machine Learning Sample

Some machine learnings example for my activity on freeday XD Built in with Scikit-learn library

6 Algorithms Used on This Project

  1. KNN
  2. Logistic Linear
  3. Decission Tree Classifier
  4. SVM
  5. Gaussian NB
  6. Linear Discrimination Analysis

2 Evaluate Models For The Datasets

  1. K Fold CV ( K Fold Cross Validation )
  2. LOOCV ( Leave One Out Cross Validation )

How it choose it's own best algorithm

There are 2 evaluate models in this project. Each models produce an array that filled up with 6 models and it's accuracy score. So it'll look for the best one and pick it up as the algorithm to use.

Next Step?

  1. Glass Classification Section
  2. Image Classification with default datasets from scikit-learn itself
  3. Maybe fixed the method of choosing the best algorithm, because sometimes there are 2 algorithms that had same score. So it may use both of them and show it's result.

Author

Robby Muhammad Nst
OrionStark