correlation-matrix

A JavaScript library to allocate and optimize financial portfolios.

Network Analysis for Financial Markets

Examples and demos showing how to call functions from the NAG Library for Python

📊🎨 Nice looking financial chart examples.

A bayesian approach to examining default mode network functional connectivity and cognitive performance in major depressive disorder

Implementation of SVM Classifier To Perform Classification on the dataset of Breast Cancer Wisconin; to predict if the tumor is cancer or not.

📊 A financial correlations library for Elixir, fully compatible with the elixir Decimal library.

Geospatial Data Digester Prototype -- a combination of interactive filtering, score generation and map plotting

collection of utility functions for correlation analysis

Different modeling techniques like multiple linear regression, decision tree, and random forest, etc. will be used for predicting the concrete compressive strength. A comparative analysis will be performed to identify the best model for our prediction in terms of accuracy. The best model will be helpful for civil engineers in choosing the appropriate concrete for bridges, houses construction.

Compute multiple types of correlations analysis (Pearson correlation, R^2 coefficient of linear regression, Cramer's V measure of association, Distance Correlation,The Maximal Information Coefficient, Uncertainty coefficient and Predictive Power Score) in large dataframes with mixed columns classes(integer, numeric, factor and character) in parallel backend.

Package for the simulation of random correlation matrix

Car Price Prediction

Implementation of the paper https://arxiv.org/abs/1909.10140 proposed correlation function.

A comprehensive analysis of XYZ Company's recent marketing campaigns starting with Python and ending with a Tableau dashboard.

Multi-Linear-Reg

Exploring correlations in an isobaric labeling mass spectrometry-based proteomic data set

Statistical Multivariate Regression Analysis to determine the effects of mortality, economic and social factors on life expectancy.

Prediction of Miles per gallon (MPG) Using Cars Dataset

A repository of scripts that can be used to create some of the most popular data visualizations at PBCAR

Repo where different methods for price regression are used (supervised machine learning)

Find and Compute optimal submatrix of invalid correlation matrix

Comparing the progress of the Corona Virus with trends in Google and Twitter.

Implementation of the correlation matrix estimator using shrinkage technique with clustering.

Linear Regression to identify the important physicochemical properties of the substrate that influence the aerial biomass production in the Cape Fear Estuary.

Exploratory Data Analysis and Visualization-GDP is one of the most important indicator in determining the performance of country economy.The significant factors affecting gdp are population,agriculture,service,industry,health,migration,urban and obesity which are recorded in the dataset. Null hypothesis is that population,agriculture,service,industry,health,migration,urban and obesity are the factors not affecting the gdp per capita of the countries. By analyzing the data we have to find out whether or not these factors affecting gdp per capita of the country. For undergoing the analysis,we have used CIA_Factsheet dataset that records different factors affecting gdp of the countries for the year 2016.Briefly factors has been described and stated hypothesis has been validated.

Analyze data from bike sharing services to identify usage patterns. Implement visual analysis, hypothesis testing, and time series analysis

Clustering project for assessment of Unsupervised Learning lecture (Jacek Lewkowicz)

Cryptocurrency classification system using dimensionality reduction with PCA & t-SNE and cluster analysis with K-Means

Methods and estimators for correcting correlation matrices spectrum in some specific cases