FAQ on Machine Learning

We can use a custom iterative sampling such that we continuously add samples to the train set. We only should keep in mind that the sample used for validation should be added to the next train sets and a new sample is used for validation.   When working with time-series data in machine learning, the … Read more

A pipeline is a sophisticated way of writing software such that each intended action while building a model can be serialized and the process calls the individual functions for the individual tasks. The tasks are carried out in sequence for a given sequence of data points and the entire process can be run onto n … Read more

The hamming distance is measured in case of KNN for the determination of nearest neighbours. Kmeans uses euclidean distance.   In the case of k-Nearest Neighbors (KNN), the distance typically measured is the Euclidean distance. Euclidean distance is a measure of the straight-line distance between two points in a Euclidean space. However, depending on the … Read more

Maximum likelihood equation helps in estimation of most probable values of the estimator’s predictor variable coefficients which produces results which are the most likely or most probable and are quite close to the truth values.   In logistic regression, the maximum likelihood estimation (MLE) is used to determine the optimal values for the model parameters. … Read more

A categorical predictor can be treated as a continuous one when the nature of data points it represents is ordinal. If the predictor variable is having ordinal data then it can be treated as continuous and its inclusion in the model increases the performance of the model. Treating a categorical variable as a continuous variable … Read more