CPSC 303: Numerical Approximation and Discretization (2015W T2)

Solution for OpenAI discretization environment

This project is an initiative to define several basic neutral file formats to facilitate exchange of meshes (as in FEM) between different SW packages.

Evenly spaced piecewise linear interpolation of functions represented using symbols in Python

📝 ML Paper implementation of machine learning paper, chimerge

Notes on discretization and numerical solutions to differential equations

Classification by Voting Feature Intervals in Python

Discretize VAR(1) of arbitrary size, with arbitrary covariance matrix for innovations, and optional stochastic volatility.

Anomaly detection with SECODA for the R environment. SECODA is a general-purpose unsupervised non-parametric anomaly detection algorithm for datasets containing numerical and/or categorical attributes.

Times Series, Classification-label/image, Regression

Discretization of numeric literals in RDF via SPARQL

The project encompasses the building of a data classification and clustering system, followed by EDA - Exploratory Data Analysis, and is concluded with the presentation of the results.

Assignments, Projects and other course related material.

Exploration of the different phases of Data Mining: Data visualization, their preprocessing and the implementation of multiple algorithms for Data Mining.

Implementing Fuzzy Inference System using PerCapitaViolentCrimesPrediction dataset where Genetic Algorithm used for feature selection, and discretizing the data while encoding values to class variables. Generating Rules with Decision Tree Classifier, And fuzzifying values and rules inference system and defuzzification in MATLAB.

An application of time series data discretization and episode mining techniques on stock price data.

these concepts are useful for converting numerical data to categorical