Day: August 22, 2019

Applied Data Science Coding with Python: How to get Classification LogLoss Metric

Applied Data Science Coding with Python: How to get Classification LogLoss Metric LogLoss, also known as logarithmic loss, is a performance metric commonly used in classification problems. It measures the difference between predicted probability and the true label. In simple terms, it calculates the error rate between the predicted values and the actual values. The …

Applied Data Science Coding with Python: How to get Classification Confusion Matrix

Applied Data Science Coding with Python: How to get Classification Confusion Matrix A confusion matrix is a table that is often used to describe the performance of a classification model on a set of test data for which the true values are known. The matrix is used to visualize the model’s predictions and compare them …

Applied Data Science Coding with Python: How to get Classification AUC ROC

Applied Data Science Coding with Python: How to get Classification AUC ROC AUC-ROC (Area Under the Receiver Operating Characteristic curve) is a commonly used metric to evaluate the performance of a binary classification model. It is a graphical representation of the model’s ability to distinguish between the two classes, and it can be used to …

Applied Data Science Coding in Python: How to get Classification Accuracy

Applied Data Science Coding in Python: How to get Classification Accuracy Classification accuracy is a measure of how well a machine learning model is able to correctly predict the class of a given data point. In other words, it tells us what proportion of the predictions made by the model are correct. It is a …