Random forest

We are going to use the same dataset we used in the Personal Cancer Diagnosis artile that was publised earlier

We will not be dealing with the exploratory data analysis but will straight go ahead with the machine learning model implementation of the dataset.

In Random Forests we have

  • Decision…

Logisitc regression ==> simple Algorithm

Naive Bayes ==> No geometric intuition. Learnt it through Probabilistic technique

Logistic Regression can be learnt from three perspectives

  • Geometric intuition
  • probabilistic approach which involves dense mathematics
  • Loss minimization framework

Assumption

  • Classes are linearly or almost linearly seperable plane

Janardhanan a r

In the making Machine Learner programmer music lover

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