correlation-matrices | Topic | Ecosyste.ms: Repos

Topic: "correlation-matrices"

GGiecold-zz/pyRMT

Python for Random Matrix Theory: cleaning schemes for noisy correlation matrices.

Language: Python - Size: 69.3 KB - Last synced at: about 2 years ago - Pushed at: over 7 years ago - Stars: 67 - Forks: 25

nk412/corella

Beautiful correlation plots for the terminal

Language: Python - Size: 696 KB - Last synced at: 27 days ago - Pushed at: about 2 years ago - Stars: 60 - Forks: 3

GGiecold/pyRMT

Python library for Random Matrix Theory, cleaning schemes for correlation matrices, and portfolio optimization

Language: Python - Size: 8.79 KB - Last synced at: 9 months ago - Pushed at: almost 3 years ago - Stars: 45 - Forks: 17

bukson/nancorrmp

Parallel correlation calculation of big numpy arrays or pandas dataframes with NaNs and infs.

Language: Python - Size: 28.3 KB - Last synced at: 26 days ago - Pushed at: over 1 year ago - Stars: 24 - Forks: 5

open-risk/correlationMatrix

correlationMatrix is a Python powered library for the statistical analysis and visualization of correlations

Language: Python - Size: 8.01 MB - Last synced at: about 1 month ago - Pushed at: 5 months ago - Stars: 14 - Forks: 6

NisanurBulut/MatlabImageProcessing

Adding Noise Noise Canceling Image resizing Resolution Study Filtering processes -Midic filter -Mean filter -Laplasian filter Photo Sharpening

Language: MATLAB - Size: 20.5 KB - Last synced at: 24 days ago - Pushed at: about 4 years ago - Stars: 9 - Forks: 1

Earnix/Correlation-Matrix-K

Сorrelation matrix UI component for Swing

Language: Java - Size: 324 KB - Last synced at: about 2 years ago - Pushed at: over 6 years ago - Stars: 6 - Forks: 2

numericalalgorithmsgroup/NAGJavaExamples

Examples demonstrating the nAG Library for Java

Language: Java - Size: 5.63 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 5 - Forks: 3

elayden/plot-corrmat

A Matlab utility for plotting correlation matrices, with similar appearance to Seaborn in Python.

Language: MATLAB - Size: 600 KB - Last synced at: about 2 years ago - Pushed at: about 5 years ago - Stars: 5 - Forks: 1

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.

Language: HTML - Size: 286 MB - Last synced at: 12 months ago - Pushed at: about 7 years ago - Stars: 5 - Forks: 3

torrentg/ccruncher

Portfolio credit risk modeling

Language: C++ - Size: 48.7 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 2 - Forks: 1

y656/Data-Analytics-model-on-Behavioural-Challenges-of-ASD-kids

This repository contains Exploratory Data Analysis in Python on Autism Behavioural Challenges on children(0-18 years) dataset

Language: Jupyter Notebook - Size: 1.05 MB - Last synced at: over 1 year ago - Pushed at: almost 3 years ago - Stars: 2 - Forks: 2

shubhammandhare10/Analyzing-Forecasting-Stock-Prices

Forecasting time series data using ARIMA models. Used covariance matrix to find dependencies between stocks.

Language: R - Size: 86.9 KB - Last synced at: over 1 year ago - Pushed at: about 3 years ago - Stars: 2 - Forks: 0

Foroozani/NEK5000_postproc

:bar_chart: Visualization of flow structure in cylinder

Language: Jupyter Notebook - Size: 2.75 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 2 - Forks: 0

SyedIkram/CryptoIntel

CryptoIntel is a one stop dashboard which gives all the information about cryptocurrencies. All the inquisitive users can get their answers related to cryptocurrencies from cryptointel.

Language: HTML - Size: 136 MB - Last synced at: about 2 years ago - Pushed at: about 6 years ago - Stars: 2 - Forks: 0

vivek2319/Linear-Regression-Prediction

This repository focuses on the projects that I would be doing on "Linear Regression". Feel free to make any improvements. Thanks

Language: Jupyter Notebook - Size: 271 KB - Last synced at: over 1 year ago - Pushed at: almost 7 years ago - Stars: 2 - Forks: 3

Marwolaeth/polychoric 📦

Instant Polychoric and Polyserial Correlation

Language: C++ - Size: 2.56 MB - Last synced at: 11 days ago - Pushed at: 11 days ago - Stars: 1 - Forks: 0

samperochkin/learning-block-exchangeability

Some code related to our paper Per,Duc,Nes. Detection (2019). The objective is to detect block-exchangeable structures in correlation matrices. For any help, please contact me or leave a comment somewhere. I will be glad to help you.

Language: R - Size: 11.5 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0

alexteghipco/Correlogram

Create beautiful tiles of scatterplots between variables in MATLAB

Language: MATLAB - Size: 1.55 MB - Last synced at: about 1 month ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

Elliott-dev/Stock_Correlation-Analysis

In this Notebook, I analyze the following five semiconductor stocks: HD, INTC, AMD, MU, NVDA, and TSM. Then, I choose the stock with the least correlation to JNJ in order to diversify a portfolio. The data was generated using the GOOGLEFINANCE historical market data script.

Language: Jupyter Notebook - Size: 1.3 MB - Last synced at: about 2 years ago - Pushed at: about 3 years ago - Stars: 1 - Forks: 0

vedanty3/heart-disease-prediction

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%)

Language: Jupyter Notebook - Size: 1.72 MB - Last synced at: 7 months ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 1

puya-pakshad/SecurityAttackTypeDataset

The purpose of these datasets is to recognize the importance of the relationships between complexity and vulnerability metrics used in identifying software security vulnerabilities and their security attack types at the function level. Using these datasets as input to machine learning and deep learning models can be developed top security vulnerability detection models with high accuracy.

Size: 2.2 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 0

abhishek1377/Customer-LifetTime-Value-Prediction

CLV prediction using Regression Analysis of customer invoice data for an online retail store

Size: 176 KB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 0

sarathchandrikak/Google-Data-Analytics-Capstone

Google Analytics Capstone Project - Bellabeat Smart Watch Analysis.

Language: HTML - Size: 32.7 MB - Last synced at: almost 2 years ago - Pushed at: almost 4 years ago - Stars: 1 - Forks: 0

Bilal092/informativeness

Infromativeness Code

Language: Python - Size: 36.1 KB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 1 - Forks: 0

rmasoudi/stone-classification

Comparing results of SVM and decision trees in stone classification

Language: C# - Size: 6.02 MB - Last synced at: over 1 year ago - Pushed at: about 6 years ago - Stars: 1 - Forks: 0

anthonyc1/data-visualization

Interactive data visualizations for Kaggle Brooklyn Home Sales data, built using D3.js

Language: JavaScript - Size: 28.8 MB - Last synced at: over 1 year ago - Pushed at: over 6 years ago - Stars: 1 - Forks: 1

khorihutama/findDistance

Finding Covariance Matrix, Correlation Coefficient, Euclidean and Mahalanobis Distance

Language: Python - Size: 24.4 KB - Last synced at: over 1 year ago - Pushed at: over 6 years ago - Stars: 1 - Forks: 1

jchambyd/FeatureSelection

Algorithms for feature selection based on covariance matrix.

Language: Java - Size: 56.4 MB - Last synced at: almost 2 years ago - Pushed at: over 7 years ago - Stars: 1 - Forks: 2

Mathiris/Forecasting

this projet is a homemade projet to explore posibilities of machine learning for forcasting issues

Language: Jupyter Notebook - Size: 1.84 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0

TongyuanBai/Change_point_correlation_matrices

Language: Python - Size: 34.2 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

maxbiostat/cladeCorrelation

Code for calculating correlations between clade indicators.

Language: R - Size: 32.2 KB - Last synced at: 25 days ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

amalsebastian7/NETWORK-OF-INFLUENCE-ON-THE-STOCK-MARKET-AND-ITS-IMPACT-ON-RISK-ANALYSIS

The goal of this research is to better understand the relationships between cryptocurrencies and stock indexes, including how cryptocurrencies are interconnected. Preliminary visualization revealed a trend of market movement across all cryptocurrencies, indicating a substantial correlation. Initial analysis focusses on finding the correlation between the stock indexes and cryptocurrencies value returns. Another objective is to study the volatility of the asset value measured by standard deviation of each asset for a short period and to further calculate the correlation between them. In order to express relationships between assets in a pictorial format, graphs are used. The assets are represented by the graph vertices, and the relationships between them are shown by edges in the graph. Further, centrality is crucial in identifying important nodes. Two measures will be considered, Eigen-vector centrality (measuring likelihood of visitation to a node) and betweenness centrality (counting the instance in which counts the instances in which a node acts as a bridge facilitating the quickest and shortest route between two nodes). The tests were carried out on four indexes (three stock indexes and one crypto index) and six well-known cryptocurrencies based on the quantity and accessibility of historical trading data. The results of the research based on the time series of price returns, points to a strong relationship between Ethereum and Bitcoin in cryptocurrencies, but Dow Jones and S&P 500 have the strongest correlation when it comes to stock indices. The moving average of volatility showed that cci30 is highly volatile compared to other stock indexes and all six crypto currencies are highly volatile. The network graph demonstrates the interconnectedness and clustering of the selected cryptocurrency currencies. It’s evident that Bitcoin functions as a central node, which means it has the highest likelihood of appearing on a random path in the graph.

Language: Mathematica - Size: 3.03 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0