Search Results for "chart"

MLJ (Machine Learning in Julia) is a toolbox written in Julia providing a common interface and meta-algorithms for selecting, tuning, evaluating, composing, and comparing about 200 machine learning models written in Julia and other languages. The functionality of MLJ is distributed over several repositories illustrated in the dependency chart below. These repositories live at the JuliaAI umbrella organization.

AutoViz is a Python data visualization library designed to automate exploratory data analysis by generating multiple visualizations with minimal code. The primary goal of the project is to help data scientists and analysts quickly understand patterns, relationships, and anomalies within datasets without manually writing complex plotting code. With a single command, the library can automatically generate dozens of charts and graphs that reveal insights into the structure and quality of the...

This project is for the development of PLC programming best practices. Based on expert input, a free video series will be developed by http://BIN95.com In this project we will start with the most basic 'start stop' ladder logic, then on to 'motor control' etc., working our way up to use of advanced instructions and tecniques. All along we will be using most common real world applications in PLC programming tutorial videos.

...Since updating the structure is a costly task, we use new data to primarily adapt the parameters and only if this is really necessary, do we adapt the structure. The method for handling concept drift is based on the Shewhart P-Chart. Project homepage: http://adpreqfr4sl.sourceforge.net

Function 1. classifier_knn 2. accuracy_knn Description 1. Returns the estimated label of one test instance, the k nearest training instances, the k nearest training labels and creates a chart circulating the nearest training instances (chart 2-D of the first two features of each instance). 2. Returns the estimated labels of one or multiple test instances and the accuracy of the estimates.