Machine Learning

In this current post, we go into the exploration and analysis of various regression machine learning methods. Our objective is to utilize a range of machine learning techniques to forecast the load demand of the Cyprus power system. In the initial phase, the ‘data’ dataframe include all essential features and measurements spanning a 16-month period. …

Deploying Diverse Regression Machine Learning Algorithms: An Implementation Overview Read More »

following the previous article about handle cyclical features, feature scaling is also important when we are going to use a machine learning algorithms. Is a method to scale the features in a comparative form. But, how can we scaling it ? what is the difference between normalization and standardization ? and when we can use …

Feature Scaling (Normalisation and Standardisation) / Python implementation Read More »

Often in situations of use machine learnings methods, we have to consider how to handle the cyclic features. For example in K-Means algorithm it use Euclidean distance in order to sort the available data’s in clusters. In this situations the distance between the hour 0 (00:00) from 23 (23:00) is bigger than what really is. …

How to handle cyclical features, for distance methodologies like k-means machine learning algorithms Read More »