There are 1 repository under correlation-matrices topic.
Python for Random Matrix Theory: cleaning schemes for noisy correlation matrices.
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
correlationMatrix is a Python powered library for the statistical analysis and visualization of correlations
Adding Noise Noise Canceling Image resizing Resolution Study Filtering processes -Midic filter -Mean filter -Laplasian filter Photo Sharpening
A Matlab utility for plotting correlation matrices, with similar appearance to Seaborn in Python.
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.
Examples demonstrating the NAG Numerical Library for Java
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 Decision Making course at Rutgers University.
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 the likely coming costs of terrorism so that resources can be set aside, in advance, to rebuild after inevitable and unfortunate attack.Although governments can submit their own internal security data to us for study, our models are constructed using the Global Terrorism Database (GTD) maintained by the National Consortium for the Study of Terrorism and Responses to Terrorism at the University of Maryland ( http://start.umd.edu/gtd/ ).
This repository contains Exploratory Data Analysis in Python on Autism Behavioural Challenges on children(0-18 years) dataset
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.
:bar_chart: Visualization of flow structure in cylinder
Forecasting time series data using ARIMA models. Used covariance matrix to find dependencies between stocks.
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.
This repository focuses on the projects that I would be doing on "Linear Regression". Feel free to make any improvements. Thanks
The objective is to use the dataset to explore the relationship between cardiac disease, body measurements, blood markers, and lifestyle choices.
CLV prediction using Regression Analysis of customer invoice data for an online retail store
Create beautiful tiles of scatterplots between variables in MATLAB
Interactive data visualizations for Kaggle Brooklyn Home Sales data, built using D3.js
Infromativeness Code
A New Parametrization of Correlation Matrices
Algorithms for feature selection based on covariance matrix.
Finding Covariance Matrix, Correlation Coefficient, Euclidean and Mahalanobis Distance
Instant Polychoric and Polyserial Correlation
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.
Comparing results of SVM and decision trees in stone classification
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.
Google Analytics Capstone Project - Bellabeat Smart Watch Analysis.
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%)
Python with Tableau