A beginners tutorial for using Python for exploratory analyses

A beginners tutorial for using R for exploratory analyses

Package implements a number local outlier factor algorithms for outlier detection and finding anomalous data

Clustering on gene expression array.

Ricerca di valori outlier nel caso univariato applicando diversi metodi (COMING SOON)

Verified the robustness to outliers of Huber Loss with Hinge loss for classification over different datasets.

Beyond Outlier Detection: LookOut for Pictorial Explanation

python package for handling nan's and outliers

Applied analysis on the Bayesian student-t "Robust" regression model with Jeffrey's prior. Compared its model performance and robustness of posterior distributions with the Gaussian model when outliers are present.

In statistics, an outlier is an observation point that is distant from other observations. How we can filter out these values using python?

Predicting disease spread, a DrivenData competition. I'am currently participating in this competition. I used it as submission for the second capstone project in the course 'Professional Certificate in Data Science' provided by Harvard University (HarvardX) on EDX.

A simple linear model fiited over Boston-House Dataset having 506 datapoints.

Prediction model for hourly bicycle utilization - task assignment

A MATLAB function for robust non-linear least squares

In this repository, using the statistical software R, are been analyzed robust techniques to estimate multivariate linear regression in presence of outliers, using the Bootstrap, a simulation method where the construction of sample distribution of given statistics occurring through resampling the same observed sample.

Single Cell Outlier Selector - quickly find outliers in your single-cell data