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Sigmoid_Neurons

Can we achieve better accuracy that SKLearn built-in functions?

Answer is Yes. In this notebook, I will demonstrate how Sigmoid Neurons implemented from scratch can provide better accuracy than SKLearn built-in Logistc Regression funtion.

SKLearn Logistic Regression implements Sigmoid curve for classification. However, it is more generalised. A Sigmoid Neuron implemented from scratch gives better accuracy(5-7% better accuracy) over SKLearn LogisticRegresstion funtion.

Accuracy Achieved:

  1. SKLearn LogisticRegression: 89.47368421052632 %
  2. Sigmoid Neurons: 94.73684210526315 %

Improvement in accuracy of Sigmoid Neurons over SKLearn LogisticRegression = 5.263157894736835 %

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This is the code for Sigmoid Neuron from scratch. It compares the model with Logistic regression (from SKLearn package)

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