Python for Random Matrix Theory: cleaning schemes for noisy correlation matrices.
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Updated
Feb 5, 2018 - Python
Python for Random Matrix Theory: cleaning schemes for noisy correlation matrices.
Python library for Random Matrix Theory, cleaning schemes for correlation matrices, and portfolio optimization
correlationMatrix is a Python powered library for the statistical analysis and visualization of correlations
Parallel correlation calculation of big numpy arrays or pandas dataframes with NaNs and infs.
This repository should help people that would like to code in R and work with the National Health and Nutrition Examination Survey (NHANES). Some topics corved are SQL , logistic regression.... etc
This repository focuses on the projects that I would be doing on "Linear Regression". Feel free to make any improvements. Thanks
Beautiful correlation plots for the terminal
JED is a program for performing Essential Dynamics of protein trajectories written in Java. JED is a powerful tool for examining the dynamics of proteins from trajectories derived from MD or Geometric simulations. Currently, there are two types of PCA: distance-pair and Cartesian, and three models: COV, CORR, and PCORR.
My fictitious firm, GDSMC Global, is a security consultancy focusing on supporting governments around the world in understanding, predicting, and stopping terrorism attacks. Our goal is to allow individual nation states to better deploy security resources to reduce the likelihood of successful terrorism in the future, and to understand what are …
Examples demonstrating the NAG Numerical Library for Java
This repository contains Exploratory Data Analysis in Python on Autism Behavioural Challenges on children(0-18 years) dataset
Algorithms for feature selection based on covariance matrix.
Interactive data visualizations for Kaggle Brooklyn Home Sales data, built using D3.js
Finding Covariance Matrix, Correlation Coefficient, Euclidean and Mahalanobis Distance
Julia package for Lewandowski Kurowicka and Joe (LKJ) probability distribution on the space of correlation matrices.
Making use of R programming, the analysis is focussed on the problem which insurance providers are facing today to define their target market and plan their sale strategies which helps them increase their market share and thereby, maximize their profitability. The analysis techniques used in the project are learnt through Data Analysis and Decis…
This project aims to build a machine learning model using K-Nearest Neighbor, LogisticRegression, RandomForestClassifier to classify whether or not a person has heart disease based upon his medical attributes. (accuracy achieved : 88.52%)
A Matlab utility for plotting correlation matrices, with similar appearance to Seaborn in Python.
Adding Noise Noise Canceling Image resizing Resolution Study Filtering processes -Midic filter -Mean filter -Laplasian filter Photo Sharpening
Looking at the probability of being accepted in a graduate program using a machine learning model
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