multiple-regression

There are 1 repository under multiple-regression topic.

srafay / Machine_Learning_A-Z
Learning to create Machine Learning Algorithms
datascience dataprocessing machine-learning-algorithms machine-learning-az simple-linear-regression multiple-regression polynomial-regression support-vector-regression decision-tree-regression random-forest-regressor classification-algorithims logistic-regression k-nearest-neighbors support-vector-machine kernel-svm naive-bayes-classifier decision-tree-classifier random-forest-classifier k-means-clustering k-means-implementation-in-python
Language:Python 385
dominance-analysis / dominance-analysis
This package can be used for dominance analysis or Shapley Value Regression for finding relative importance of predictors on given dataset. This library can be used for key driver analysis or marginal resource allocation models.
classification-model dominance dominance-analysis dominance-statistics feature-engineering feature-importance feature-selection keydrivers logistic-regression multiple-regression predictor predictor-importance pseudo-r-square r-square regression-models relative-importance shapley-value
Language:Python 160
agrawal-priyank / machine-learning-regression
Built house price prediction model using linear regression and k nearest neighbors and used machine learning techniques like ridge, lasso, and gradient descent for optimization in Python
linear-regression multiple-regression house-price-prediction ridge-regression polynomial-regression gradient-descent python machine-learning machine-learning-regression coursera university-of-washington
Language:Jupyter Notebook 92
hunar4321 / RLS-neural-net
Recursive Leasting Squares (RLS) with Neural Network for fast learning
neural-network machine-learning oneshot-learning oneshotlearning kalman-filter artificial-intelligence multiple-regression recursive-least-squares regression-analysis
Language:Jupyter Notebook 53
EvanDietrich / Quant-Finance-Projects
Quantitative Finance & Statistics Projects. Topics including multiple linear regression, variance and instability estimates, display methodology.
linear-regression regression-analysis instability regression-models deviations variance market-analytics multiple-regression quant-finance
Language:Jupyter Notebook 52
vsoch / regression-wasm
Testing doing basic regression with web assembly
golang linear-regression multiple-regression wasm web-assembly
Language:Go 32
ditikrushna / Predict-Sales-Revenue-Using-Multiple-Regression-Model
In this project you will build and evaluate multiple linear regression models using Python. You will use scikit-learn to calculate the regression, while using pandas for data management and seaborn for data visualization. The data for this project consists of the very popular Advertising dataset to predict sales revenue based on advertising spending through media such as TV, radio, and newspaper.
data-science regression-models multiple-regression multiple-regression-analysis seaborn
Language:Jupyter Notebook 24
Amitha353 / Machine-Learning-Regression
Machine-Learning-Regression
simple-linear-regression multiple-regression gradient-descent coordinate-descent ridge-regre lasso-regression nearest-neighbor-search kernel-regression loss-functions bias-variance-tradeoff cross-validation generalization-error overfitting coefficient-path polynomial-regression
Language:Jupyter Notebook 17
Lunarestia / MAT243-Applied-Statistics-for-STEM-I
PYTHON- Projects in my MAT-243 STATS for STEM I course at SNHU (HTML files and Python files with source code and reports)
python python-3 python-script statistics jupyter-notebook regression-models regression-analysis regression-testing regression-tests regression multiple-regression multiple-linear-regression linear-regression
Language:HTML 6
BradyFisher / R-Projects
A collection of some of my R Projects
anova multiple-logistic-regression multiple-regression r r-markdown simple-logistic-regression simple-regression two-sample-t-test variable-selection
3
cgatama / 7-Data-Analysis-with-Python
Data analysis with Python to building and evaluating data models.
collecting-data data-pipelines exploratory-data-analysis formatting-data importing-and-cleaning-data linear-regression machine-learning-regression model-refinement multiple-regression numpy pandas-library polynomial-regression preparing-data scikit-learn scipy summarizing-data dataframe-manipulation
Language:Jupyter Notebook 3
hunar4321 / multiple-regression
A simple intuitive method for multiple regression
linear-regression machine-learning multiple-regression numpy predictive-modeling python regression
Language:Jupyter Notebook 3
Real-Estate-Statistical-Modeling
griffinbran / Real-Estate-Statistical-Modeling
Predictive analysis, with feature engineering, and machine learning (ML) algorithms, such as linear regression, applied to predict the final sale price of homes in Ames, IA from 2006-2010.
kaggle-submission correlation-analysis feature-engineering sklearn p-values cross-validation hypothesis-testing one-hot-encoding multiple-regression linear-models imputed-values outlier-detection
Language:Jupyter Notebook 2
ML_Regression
jeremywood-ai / ML_Regression
Examples of Machine Learning Regression Models Built in Python and R
decision-tree machine-learning multiple-regression python3 r regression-models svm
Language:Python 2
kamlesh0928 / machine-learning
This repository contains machine learning algorithms implemented from scratch and using scikit-learn, covering classification, regression, and clustering. Each algorithm is well-documented, with clear code and explanations. To use K-Medoids, install sklearn_extra via pip install scikit-learn-extra. Contributions are welcome!
decision-tree-classifier linear-regression logistic-regression multiple-regression naive-bayes-classifier dbscan-clustering hierarchical-clustering kmeans-clustering kmedoids-clustering knn-classifier lda pca polynomial-regression support-vector-machine
Language:Python 2
KhushiBhadange / Regression-Models
In this repository, delve into the realm of regression modeling featuring an array of algorithms applied to diverse datasets. Explore the strengths and nuances of different regression techniques, providing a comprehensive overview for anyone interested in predictive modeling.
feature-engineering feature-selection linear-regression machine-learning-regression multiple-regression polynomial-regression predictive-modeling predictive-modeling-techniques regression regression-analysis regression-models regression-technique data-science-regression
Language:Jupyter Notebook 2
udialter / equivalence-testing-multiple-regression
I constructed a simulation study to evaluate the statistical performance of two equivalence-based tests and compared it to the common, but inappropriate, method of concluding no effect by failing to reject the null hypothesis of the traditional test. I further propose two R functions to supply researchers with open-access and easy-to-use tools that they can flexibly adopt in their own research.
psychology quantitative-methods multiple-regression equivalence-testing null-hypothesis quantitative-psychology
2
acanacar / DataScienceOverHood
DataScienceOverHood
bayesian-regression deep-neural-networks house-price-prediction keras multiple-regression ols-regression python3 regression-models ridge-regression rnn
Language:Jupyter Notebook 1
AprajitaChhawi / Data-Science
Data Science from the very basics along with some projects
linear-regression multiple-regression data-science scikit-learn enclosing-data market-basket-analysis logistic-regression
Language:Jupyter Notebook 1
ashemsu / statistical-programming-R
This repo includes the beginning of my more advance project work during my undergraduate program at UPenn, wherein we to applied statistical concepts into our analysis in R.
binary-classification correlation-analysis data-wrangling heteroskedasticity-consistent-standard-errors hypothesis-testing machine-learning model-validation monte-carlo-simulation multiple-regression predictive-analytics probability-distribution r-programming r-studio regression-analysis statistical-analysis statistical-models statistical-programming survey-analysis time-series-analysis robust-standard-error
1
david-fried / Investigating_Chicago_Crime
Investigated the influence of economic, birth, and health factors on Chicago neighborhood homicide rates using correlation, simple regression, and multiple regression analyses. Created a heatmap to visualize differences in homicide rates between Chicago neighborhoods.
3d-visualization matplotlib pandas python3 numpy multiple-regression jupyter-notebook api gmaps-api chicago-neighborhoods neighborhood-homicide neighborhood-crime-heatmap
Language:Jupyter Notebook 1
geethanjali-2003 / Red_Wine_Quality_SDA_Project
data-analysis multiple-regression r-script hypothesis-testing
Language:R 1
Gkontopodis / Regression-Modelling-in-Practice
Wesleyan University
python linear-regression multiple-regression logistic-regression
Language:Python 1
Hariharan-SV / Futurist
Used Car Price Prediction Package
machine-learning car-price-prediction multiple-regression random-forest python colab-notebook
Language:Jupyter Notebook 1
iamkotwala / DataScience
A repo for all my Data-Science ipynbs. Helpful for someone who wants to start with the basics of Data Science (Stats, ML, DL)
data-science kmeans-clustering multiple-regression neural-network statsmodels tensorflow2
Language:Jupyter Notebook 1
jianwenwu / STAT-72456-Statistical-Learning-2018
multiple-regression
Language:Jupyter Notebook 1
jiheon788 / agricultural-price-forecasting-model
아주대학교 2021-2 비즈니스 애널리틱스 프로젝트
random-forest machine-learning data-visualization eda lstm multiple-regression prophet vectorautoregression
Language:Jupyter Notebook 1
priyankag1194 / Stock-Market-Analysis
The MATLAB code analyses stock prices of a company and predicts the closing price. The algorithms implemented for predicting closing price are: (a)Kalman Filter (b)Kalman Multiple Linear Regression The algorithms implemented for analysing the trends in a stock (c) Bollinger bands (d). Chaikin Oscillator Output - 1. Graphs showing the predicted and actual values of closing price of stock anlong with bollinger bands 2. The chaikin oscillator graph 3. %accuracy of prediction of Kalman and MLR filter The stock_analysis.zip file contains the following - 1. Code (a)stock_analysis.m (b).kalman1.m (c)bollinger.m (d)multiple_linear_regress.market (e). chaikin.m (f).ma_filter.m 2. Data - 2 .mat files having opening,closing, high,low and volume of a stock (a) comp_1.mat and (b)comp_2.mat To run the stock market analysis code - 1.Run stock_analysis.m 2.Enter file name
stock-price-prediction digital-signal-processing analysis stock-market kalman-filter chaikin bollinger-bands multiple-regression matlab
1
Ranjitkumarsahu1436 / Multiple-Regression
Multiple regression is an extension of simple linear regression. It is used when we want to predict the value of a variable based on the value of two or more other variables. The variable we want to predict is called the dependent variable (or sometimes, the outcome, target or criterion variable)
regression multiple-regression visualization matplotlib explanatory-variables independent-variables
Language:Jupyter Notebook 1
scottherford / Barley-House
Ames Housing Prices: Advanced Regression Techniques
multiple-regression cross-validation feature-selection lasso elastic-net forward-backward stepwise-regression
Language:SAS 1
rerp
sjburwell / rerp
Compute regression event-related potentials ("rERPs") which account for hypothetical overlap among brain processes accompanying temporally adjacent cognitive events (e.g., stimulus and response).
multiple-regression electroencephalogram eeg-analysis
Language:MATLAB 1
sndrake / StatsWorkshop
Workshop on two-way ANOVA and multiple regression in R, presented at the SLAT Roundtable on Feb. 8-9, 2019.
anova multiple-regression psycholinguistics r regression statistical-analysis
Language:R 1
soumenca / LinearRegression
Linear Regression and polynomial regression using Python
linear-regression multiple-regression python machine-learning algorithms
Language:Python 1
TheChanRProject / CGUMRAssignments
Repo for multiple regression assignments in Quant III for EDUC467.
hierarchical-models stepwise-regression multiple-regression logistic-regression correlation
1
ved-et9 / ML-Algo-s
📚📝 Types of Ml algos
liner-regestion machine-learning ml-models multiple-regression numpy pandas scikit-learn
Language:Jupyter Notebook 1
vjgpt / Housing-Prices-Competition-Kaggle
Learn about Feature Engineering and get familiar with Advanced regression techniques like Lasso, ElasticNet, Gradient Boosting, etc.
feature-engineering regression-models housing-prices model-analysis model-comparison multiple-regression machine-learning
Language:Jupyter Notebook 1

multiple-regression

srafay / Machine_Learning_A-Z

dominance-analysis / dominance-analysis

agrawal-priyank / machine-learning-regression

hunar4321 / RLS-neural-net

EvanDietrich / Quant-Finance-Projects

vsoch / regression-wasm

ditikrushna / Predict-Sales-Revenue-Using-Multiple-Regression-Model

Amitha353 / Machine-Learning-Regression

Lunarestia / MAT243-Applied-Statistics-for-STEM-I

BradyFisher / R-Projects

cgatama / 7-Data-Analysis-with-Python

hunar4321 / multiple-regression

griffinbran / Real-Estate-Statistical-Modeling

jeremywood-ai / ML_Regression

kamlesh0928 / machine-learning

KhushiBhadange / Regression-Models

udialter / equivalence-testing-multiple-regression

acanacar / DataScienceOverHood

AprajitaChhawi / Data-Science

ashemsu / statistical-programming-R

david-fried / Investigating_Chicago_Crime

geethanjali-2003 / Red_Wine_Quality_SDA_Project

Gkontopodis / Regression-Modelling-in-Practice

Hariharan-SV / Futurist

iamkotwala / DataScience

jianwenwu / STAT-72456-Statistical-Learning-2018

jiheon788 / agricultural-price-forecasting-model

priyankag1194 / Stock-Market-Analysis

Ranjitkumarsahu1436 / Multiple-Regression

scottherford / Barley-House

sjburwell / rerp

sndrake / StatsWorkshop

soumenca / LinearRegression

TheChanRProject / CGUMRAssignments

ved-et9 / ML-Algo-s

vjgpt / Housing-Prices-Competition-Kaggle