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machine-learning's Introduction

Machine-Learning Algorithms for Classification Problem

Included Algorithms

1. Perceptron

2. Logistic regression

3. SVM (to be added)

datasets

  1. Finance 2.Bio
  2. Vision
  3. NLP and
  4. Speech

Algorithm Details:

Perceptron classification algorithm implementation.

Algorithm Description:

  1. This algorithm uses sign function as model to predict.
  2. Stochastic Gradient Descent is used to perform online training on each input.
  3. Uses hinge loss function without hinge.
  4. Implementation accepts user arguments for learning rates.

Logistic Regression Details:

  1. Two optimization techniques added a. SGD b. Adam variant of SGD
  2. Logistic loss to caluclate loss
  3. Adam variant uses dropout to customize learning with increasing training iterations.

#SVM (to be added)

Accuracy Results

  1. Logistic:

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Contributors

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Watchers

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