We can clearly see this is a binary classifier, i.e., for example, it can be used for classifying binary datasets like predicting whether it is a male or a female using certain parameters.But we can use this logistic regression to classify multi-class problems too with some modifications. ...
if model_name == 'logistic_regression': param_dist = dict(C=loguniform(1e-6, 1e+6)) @@ -110,7 +111,7 @@ def get_param_dist(model_name): return param_dist def get_param_space(model_name): def get_param_space(model_name: str) -> Dict[str, Any]: """Get the parameter sp...
Implemented logistic regression using a neural network approach to classify images Completed Week 2 of Andrew NG's course Day 23 (1-10-18) Implemented gradient descent from scratch Implemented gradient descent form scratch Learnt more about activation functions sigmoid, tanh, ReLU and leaky ReLU Lear...
'Logistic' RegressionSigmoidMSE/Binary cross-entropy One of the most popular numerical algorithms to optimize a loss is theGradient Descent. We can mention three variants of GD:Batch gradient descent, which computes the loss function gradient for the whole training data-set ,Stochastic gradient desce...