Introduction: This is the second article on data quality, for the first part, please go to: http://laranikalranalytics.blogspot.com/2019/11/using-r-and-h2o-isolation-forest-for.html Since Isolation Forest is building an ensemble of isolation trees, and these trees are created randomly, there is a lot of randomness in the isolation forest training, ...

Introduction: We will identify anomalous patterns in data, this process is useful, not only to find inconsistencies and errors but also to find abnormal data behavior, being useful even to find cyber attacks on organizations. On this article there is more information as reference: Data Quality and Anomaly Detection Thoughts ...

Using R and H2O Isolation Forest to predict car battery failures. Carlos Kassab 2019-May-24 This is a study about what might be if car makers start using machine learning in our cars to predict falures. # Loading librariessuppressWarnings( suppressMessages( library( h2o ) ) ) suppressWarnings( suppressMessages( library( data.table ) ) )suppressWarnings( suppressMessages( library( ...

Steps Needed in a Process to Detect Anomalies And Have a Maintenance Notice Before We Have Scrap Created on The Production Line.Describing my previous articles( 1, 2 ) process flow:Get Training Data.At least 2 weeks of passed units measurements.Data Cl...

Before installing anything I signed up on https://github.com/and created my R-ANALYTICS repository:https://github.com/LaranIkal/R-ANALYTICSNow the installation and setup.1. I installed git on Ubuntu, from a terminal window:$ sudo apt-get update $ sudo apt-get install git2.- I configured git:I did this through the git ...