These models are trained on the sample data provided, which should include a variety of classes and relevant data, called factors, believed to affect the classification. These statistical models include traditional logistic regression (also known as logit), neural networks, and newer modeling techniques like RandomForest. Machine learning, at the heart of data science, uses advanced statistical models to analyze past instances and to provide the predictive engine in many application spaces. That predictive power, coupled with a flow of new data, makes it possible to analyze and categorize data in an online transaction processing (OLTP) environment. These patterns are presumed to be causal and, as such, assumed to have predictive power. Real-time classification of data, the goal of predictive analytics, relies on insight and intelligence based on historical patterns discoverable in data. Weka has a utilitarian feel and is simple to operate. Weka is an open source program for machine learning written in the Java programming language ….
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |