correlation-analysis
There are 394 repositories under correlation-analysis topic.
josevcm/nfc-laboratory
NFC signal and protocol analyzer using SDR receiver
easystats/correlation
:link: Methods for Correlation Analysis
ddz16/Preformer
This repository contains the pytorch code for the 2023 ICASSP paper "Preformer: Predictive Transformer with Multi-Scale Segment-wise Correlations for Long-Term Time Series Forecasting”
chgl16/data-mining-algorithm
:bar_chart: 数据挖掘常用算法：关联分析Apriori算法，数据分类决策树算法，数据聚类K-means算法
rajtulluri/Olist-business-analysis
A detialed analysis on the customers, products, orders and shipments of the Brazilian E-commerce giant Olist.
open-risk/correlationMatrix
correlationMatrix is a Python powered library for the statistical analysis and visualization of correlations
ckdckd145/statmanager-kr
Open-source statistical package in Python based on Pandas
jware-solutions/ggca
Blazing fast Gene/GEM Correlation Analysis for Rust and Python
vaitybharati/Assignment-04-Simple-Linear-Regression-2
Assignment-04-Simple-Linear-Regression-2. Q2) Salary_hike -> Build a prediction model for Salary_hike Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization. Correlation Analysis. Model Building. Model Testing. Model Predictions.
DivyaDevaprasad/Twitter_and_StockPrice_sem2
Twitter is an online social networking service with over 300 million monthly active users. This enormous amount of data available on social media platforms can be extracted and analyzed for various purposes. In this paper, we aim to investigate the relationship between sentiment analysis of Twitter data and stock market prices for five companies (Walmart, ExxonMobil, Apple, Berkshire Hathaway Inc., and Amazon) by scraping the Tweets extracted from Twitter based on company hashtags and using the twitter intelligence tool – twint. Sentiment analysis is applied to the extracted tweets and a correlation is analyzed between stock market movements of a company and sentiments in tweets. Elaborately, news and tweets in social media about a company would encourage decision of people to invest or not in the stocks of that company and as a result, the stock price of that company would increase or fall. At the end of the paper, it is shown that a none or very weak correlation exists between the rise and fall in stock prices with the public sentiments in tweets
kmedian/korr
collection of utility functions for correlation analysis
PARSA-MHMDI/correlation
In this repository, four famous correlation algorithms have been implemented. Pearson, spearman, Chatterjee, and MIC correlation algorithm implemented
0xd3lbow/Bitcoin-Rolling-Correlation
Time-Series Modeling of Bitcoin for Equities, Commodities & Forex Markets
lkfink/pupilTutorial
A code tutorial to accompany https://link.springer.com/article/10.3758/s13428-023-02098-1
mittelmark/snha
St. Nicolas House Algorithm implementation in R - predicting correlation networks using association chains
FirasKahlaoui/pca-insights
PCA Insights is a data analysis project aimed at applying Principal Component Analysis (PCA) to high-dimensional datasets for dimensionality reduction, visualization, and exploration.
Siddartha09/parkinsons_prediction
This repo is an attempt to diagnose Parkinson's disease using voice measurements of patients using machine learning algorithms.
vaitybharati/Assignment-05-Multiple-Linear-Regression-2
Assignment-05-Multiple-Linear-Regression-2. Prepare a prediction model for profit of 50_startups data. Do transformations for getting better predictions of profit and make a table containing R^2 value for each prepared model. R&D Spend -- Research and devolop spend in the past few years Administration -- spend on administration in the past few years Marketing Spend -- spend on Marketing in the past few years State -- states from which data is collected Profit -- profit of each state in the past few years.
vaitybharati/Assignment-11-Text-Mining-01-Elon-Musk
Assignment-11-Text-Mining-01-Elon-Musk, Perform sentimental analysis on the Elon-musk tweets (Exlon-musk.csv), Text Preprocessing: remove both the leading and the trailing characters, removes empty strings, because they are considered in Python as False, Joining the list into one string/text, Remove Twitter username handles from a given twitter text. (Removes @usernames), Again Joining the list into one string/text, Remove Punctuation, Remove https or url within text, Converting into Text Tokens, Tokenization, Remove Stopwords, Normalize the data, Stemming (Optional), Lemmatization, Feature Extraction, Using BoW CountVectorizer, CountVectorizer with N-grams (Bigrams & Trigrams), TF-IDF Vectorizer, Generate Word Cloud, Named Entity Recognition (NER), Emotion Mining - Sentiment Analysis.
2004-ind/Correlation_Analysis
Protecting portfolios using Correlation Diversification
abenton/MissingView-LasCCA
Scalable code to solve SUMCOR Generalized CCA problem with missing views.
dagiteferi/Financial-News-Sentiment-Stock-Market-Correlation-Analysis
Analyze financial news sentiment and its correlation with stock market movements. Use NLP, sentiment analysis, and financial analytics to uncover insights for enhanced financial forecasting and innovative investment strategies.
IbrahimElzahaby/MSc_Thesis
Computational protemics analysis of cancer cell-lines at the level of single-cells
jacksonwalters/scotus-v-public
Capstone project for The Data Incubator ('18). Plots SCOTUS vs. public opinion polarity over time given keywords.
Shahrukh2016/Play-store-review-analysis-EDA
Exploring Google Play Store apps dataset to identify key factors for app engagement and success, revealing correlations between reviews, installs, categories, ratings, and user preferences.
Ashfinn/Diarrhea-Prediction-Model
This research project analyzes the relationship between environmental factors and diarrheal disease incidence across four major divisions in Bangladesh.
Devanshi-Bavaria/Predictive-Modeling-for-Stock-Market-Trends
📈 Comprehensive stock price analysis, including preprocessing, clustering, correlation, and predictive modeling, to enhance investment insights and accuracy. 💡
HarryFosterCU/UN-Emissions-Regression-Analysis
Code for performing regression analysis and data visualisation on UN emission data 1970-2017
pavankethavath/Microsoft-Classifying-Cybersecurity-Incidents-with-ML
A machine learning pipeline for classifying cybersecurity incidents as True Positive(TP), Benign Positive(BP), or False Positive(FP) using the Microsoft GUIDE dataset. Features advanced preprocessing, XGBoost optimization, SMOTE, SHAP analysis, and deployment-ready models. Tools: Python, scikit-learn, XGBoost, LightGBM, SHAP and imbalanced-learn
RimTouny/Credit-Card-Fraud-Detection
Focused on advancing credit card fraud detection, this project employs machine learning algorithms, including neural networks and decision trees, to enhance fraud prevention in the banking sector. It serves as the final project for a Data Science course at the University of Ottawa in 2023.
SBouchard01/CorrHOD
A code that populates dark matter halos and computes correlation functions
tezam84/Supervised_Project_Parkinson_disease
Supervised Machine Learning project with KNN, decision tree, random forest and adaboost algorithms
vaitybharati/Assignment-04-Simple-Linear-Regression-1
Assignment-04-Simple-Linear-Regression-1. Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization, Feature Engineering, Correlation Analysis, Model Building, Model Testing and Model Predictions using simple linear regression.
vaitybharati/Assignment-05-Multiple-Linear-Regression-1
Multiple-Linear-Regression-1. Consider only the below columns and prepare a prediction model for predicting Price of Toyota Corolla.
vaitybharati/P24.-Supervised-ML---Simple-Linear-Regression---Newspaper-data
Supervised-ML---Simple-Linear-Regression---Newspaper-data. EDA and Visualization, Correlation Analysis, Model Building, Model Testing, Model predictions.
wonderakwei/sales-marketing-data-analytics-using-python
This project utilizes Python, employing regression and correlation analysis to optimize marketing campaigns. By analyzing sales impact across different hospital account types, it unveils key strategies, culminating in actionable recommendations and a comprehensive ROI table for effective decision-making.