Topic: "statsmodels"
ashishyadav24092000/TukeyKramerTest_MultiComparisonOFMEAN
It compares the pair of mean tensile strength having significantly equal means using tukey cramer test. It will further help us to improve our decisions based on this insight at the production and design side.
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tboudart/Life-Expectancy-Regression-Analysis-and-Classification
I contributed to a group project using the Life Expectancy (WHO) dataset from Kaggle where I performed regression analysis to predict life expectancy and classification to classify countries as developed or developing. The project was completed in Python using the pandas, Matplotlib, NumPy, seaborn, scikit-learn, and statsmodels libraries. The regression models were fitted on the entire dataset, along with subsets for developed and developing countries. I tested ordinary least squares, lasso, ridge, and random forest regression models. Random forest regression performed the best on all three datasets and did not overfit the training set. The testing set R2 was .96 for the entire dataset and developing country subset. The developed country subset achieved an R2 of .8. I tested seven different classification algorithms to classify a country as developing or developed. The models obtained testing set balanced accuracies ranging from 86% - 99%. From best to worst, the models included gradient boosting, random forest, Adaptive Boosting (AdaBoost), decision tree, k-nearest neighbors, support-vector machines, and naive Bayes. I tuned all the models' hyperparameters. None of the models overfitted the training set.
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vaitybharati/P27.-Supervised-ML---Multiple-Linear-Regression---Toyoto-Cars
Supervised-ML---Multiple-Linear-Regression---Toyota-Cars. EDA, Correlation Analysis, Model Building, Model Testing, Model Validation Techniques, Collinearity Problem Check, Residual Analysis, Model Deletion Diagnostics (checking Outliers or Influencers) Two Techniques : 1. Cook's Distance & 2. Leverage value, Improving the Model, Model - Re-build, Re-check and Re-improve - 2, Model - Re-build, Re-check and Re-improve - 3, Final Model, Model Predictions.
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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.
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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.
Language: Jupyter Notebook - Size: 196 KB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 2 - Forks: 0
louisyuzhe/timeseries-forecast-automation
Automated the process of training time-series data with multiple Machine Learning and Stats Models to output the most accurate forecast result
Language: Python - Size: 53.7 KB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 2 - Forks: 3
nfultz/Intro_Dueto
~PyDataLA 2020~ talk
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Palak-15/Predict-Insurance-charges
Predict Insurance charges using feature bmi, sex, smoker, region, have children and age
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Palak-15/decline_viewership_linear_regression
Problem Statement: A digital media company (similar to Voot, Hotstar, Netflix, etc.) had launched a show. Initially, the show got a good response, but then witnessed a decline in viewership. The company wants to figure out what went wrong.
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Palak-15/Housing-Case-Study
Consider a real estate company that has a dataset containing the prices of properties in the Delhi region. It wishes to use the data to optimize the sale prices of the properties based on important factors such as area, bedrooms, parking, etc.
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AIAScience/mflux-ai-tutorials
Open source data science tutorials for MFlux.ai
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gmiretti/forecasting Fork of mscharth/forecasting
Time series analysis tutorials using Python
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Dr-Salcedo/hepatocellular_carcinoma_one_year_survival
Classification model for 1 year survival rates in patients with HCC (hepatocellular carcinoma).
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north0n-FI/Multivariate-Regression---King-County-House-Prices
Supervised Machine Learning Using Regression Analysis
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wxd/s3-2017-forecasting
Code for the S3 2017 summer school project "Who's winning it? – Forecasting sports tournaments"
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ebottabi/ml-training
ML-training
Size: 4.88 KB - Last synced at: about 1 year ago - Pushed at: almost 8 years ago - Stars: 2 - Forks: 0
JoomiK/RobberiesTimeSeries
Forecasting monthly armed robberies in Boston with an ARIMA model.
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bessarodrigo/linear-regression-salaries
Análise dos fatores que influenciam os salários dos colaboradores de uma empresa, utilizando técnicas de regressão linear múltipla.
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vineet416/Chronic-Kidney-Disease-Prediction
This repository contain code of Chronic Kidney Disease Detection Prediction Project. The goal of this project is predict the chronic kidney disease using parameters like Diabetes Mellitus, Blood Urea, Sugar, Hypertension etc.. I used multiple machine learning algorithms with hyperparameter tuning which is having highest accuracy score of 97.5
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HuangRicky/manylinux2014builds
manylinux2014 Python pkg builds
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Abdiasarsene/Analysis_And_Findings
This repository groups together various projects conducted to address specific business needs. Each project includes details on the business context, the data used, the analysis methods applied, and the results obtained. You will also find detailed notebooks, scripts, and reports for each project.
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mgckaled/ignite-devia-supervised_algorithms
Repositório que reuni os módulos 7 ao 13 da Formação Desenvolvimento IA 2023-2024, desenvolvido pela Rocketseat Education.
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ankit-kothari/Data-Science-Journey
Language: Jupyter Notebook - Size: 156 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 1 - Forks: 0
StevenRice99/LLM-Forecast
A Novel Hybridized Forecasting Technique Utilizing ARIMA and Large Language Models
Language: Python - Size: 123 MB - Last synced at: 3 months ago - Pushed at: 6 months ago - Stars: 1 - Forks: 0
ebottabi/automl
An automated machine learning toolkit.
Language: Python - Size: 8.79 KB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 1 - Forks: 1
mytechnotalent/Phone_Information_2024_Classification
Phone Information 2024 Exploratory Data Analysis & Machine Learning Classification Model
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mytechnotalent/Heart-Attack-Binary-Classifier
Heart Attack Exploratory Data Analysis & Machine Learning Binary Classification Model
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mytechnotalent/chicago-influenza-binary-classification
Data Analysis & Machine Learning w/ Chicago Inpatient, Emergency Department, and Outpatient Visits for Respiratory Illnesses
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ranja-sarkar/Time_series
Time-series Analysis
Language: Python - Size: 2.64 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 0
Akemp787/Comprehensive-Business-Performance-Analysis
This project analyzes sales and financial data using Python and Pandas to provide insights and recommendations. It includes an interactive Tableau dashboard for exploring key metrics and trends.
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psyplot/psy-reg
Psyplot plugin for visualizing and calculating regression plots
Language: Python - Size: 6.04 MB - Last synced at: 21 days ago - Pushed at: 11 months ago - Stars: 1 - Forks: 1
shreyansh-2003/Hands-On-With-Machine-Learning-Algorithms
This repository contains a collection of labs that explore various machine learning algorithms and techniques. Each lab focuses on a specific topic and provides detailed explanations, code examples, and analysis. The labs cover clustering, classification and regression algos, hyperparameter tuning, data-preprocessing and various evaluation metrics.
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dr-saad-la/Stats-Modeling-with-Python
Statistical Modeling with Python
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Mr-Atanu-Roy/Eco-Visionaries-SIH_2023
Eco Visionaries is an application that aims to provide constant monitoring of AQI and WQI for a particular study area. It is a project developed for SIH 2023
Language: Python - Size: 234 KB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 1 - Forks: 1
alansampedro/airbnb_nyc
Skills: Python (Pandas, Numpy, Matplotlib, Seaborn, Sklearn, Statsmodels)
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SamualBrusky/IQA
Stock price prediction models for alpaca.markets
Language: Python - Size: 239 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 2
ekanshojha/Time-Series-Analysis
Time Series Analysis of Airline Passenger Data, In this time series forecasting, taking data from kaggle site and applying ARIMA and SARIMAX model to evaluate seasional trends of passenger travelling via airlines.
Language: Python - Size: 52.7 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0
arachnocid/Cryptocurrency-Prediction-Model
A neural network model for predicting cryptocurrency prices using machine learning and time series analysis techniques.
Language: Python - Size: 285 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0
atharvapathak/Sales_Forecasting_Project
Forecasted product sales using time series models such as Holt-Winters, SARIMA and causal methods, e.g. Regression. Evaluated performance of models using forecasting metrics such as, MAE, RMSE, MAPE and concluded that Linear Regression model produced the best MAPE in comparison to other models
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igorastashov/price-prediction-linear-models
Предсказание стоимости автомобиля на основе разработанной линейной модели и реализация FastAPI веб-сервиса для презентации решения.
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shinho123/Boston-house-price-prediction
2022년 1학기 데이터처리언어 팀 프로젝트 : 보스턴 집값 예측 문제
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Jean-LucasLS/Regressao-Linear-2
Utilizando-se a técnica de regressão linear, com o auxílio dos frameworks scikit-learn e statsmodel, foi possível criar um modelo de predição de preços de imóveis, com base em variáveis explanatórias de um database.
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ErfanRMN/Python-for-Economics-Series
A series of practical, sufficient, and to-the-point crash courses offered at the University of Tehran, mostly for Economics students with no prior programming background.
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barquerosanchezdiegoarmando/UNA-Econometrics-I-py
Este es un repositorio con material adicional para la clase del profesor Alexander Amoretti, con el cual los estudiantes puedan trabajar y extender sus conocimientos en Python en el área de la econometría. No obstante es importante aclarar que no es un curso introductorio a Python y es necesario un nivel básico para completar en su totalidad
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aaron1rcl/multivariate_time_series_interpolation
Multivariate Time series interpolation using hierarchical mixed effects models.
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VimalChamyal/Sales-prediction-using-Simple-Linear-Regression
In this project have used Simple Linear Regression to model the data. I have tried to predict 'sales' using the 'amount spent on advertisement using TV as the medium'.
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homeez/TimeSeries_Analysis
Time Series Analysis using Statsmodels' ARIMA model
Language: Jupyter Notebook - Size: 462 KB - Last synced at: 6 months ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0
domingosdeeulariadumba/AngolaHDIvsEducationAndHealthSpendingAnalysis
Analysing the HDI and Spending of angolan government, on health and education, between 2002 and 2021.
Language: Python - Size: 8.85 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0
bala-1409/Foreign-Exchange-Rate-Time-Series-Data-science-Project
This project will use time series analysis to forecast the exchange rate between the euro and the US dollar. The project will use a variety of statistical techniques, such as ARIMA to model the data and forecast the exchange rate.
Language: Jupyter Notebook - Size: 2.39 MB - Last synced at: 3 months ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0
sloancinkle/eda
Data Science
Language: Jupyter Notebook - Size: 3.61 MB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0
paytonshafer/Car-Insurance-Claim-Outomes
This repo contains a Jupyter Notebook that determines the best single feature to predict car insurance claim outcomes.
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trthatcher/Mahalangur
Statistical insights and visualizations from the Himalayan Database 🏔️ 📊
Language: Python - Size: 11.6 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0
domingosdeeulariadumba/Kleanee_RegressionAnalysis
This project aimed at studying the relationship between the Spending Score and Age (firstly introduced in my Clustering Project).
Language: Python - Size: 4.63 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0
KevinDepedri/AI-for-Finance
Stock market prediction on 5 italian companies using VAR model, OLS regressions and LSTM recurrent neural networks over data retrieved from Refinitiv Eikon
Language: Jupyter Notebook - Size: 5.67 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0
mamomen1996/Python_CS_02
Sports Analytics in Python
Language: HTML - Size: 4.73 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0
mamomen1996/Python_CS_01
Traditional Regression problem project in Python
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fsmosca/Rating-Correlations
Predicts chess960 or crazyhouse ratings given bullet or blitz and others for either Lichess.org or Chess.com servers.
Language: Python - Size: 1.72 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0
robyndwhite/finding-where-to-thrive
Language: Jupyter Notebook - Size: 138 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0
EgorovYuriy/Yandex.Practicum_Data_Science_Projects
Language: Jupyter Notebook - Size: 1.43 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0
VladKosh1994/Statistic-practice
Mini-projects
Language: Jupyter Notebook - Size: 6.19 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0
i3house/Flight-EDA-and-Regression
Exploratory Data Analysis and build a Multiple Linear Regression Model using statsmodels module
Language: Python - Size: 1.05 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0
AlaaNabil98/Analyze-A-B-Test-Results
working to understand the results of an A/B test run by an e-commerce website. The company has developed a new web page in order to try and increase the number of users who "convert," meaning the number of users who decide to pay for the company's product.
Language: Jupyter Notebook - Size: 5.25 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0
showman-sharma/BIKE_SHARING-LIN-REG-MODEL
We want to understand the factors affecting the demand for shared bikes in the American market, based on various meteorological surveys and people's styles. We shall achieve this by building a Linear Regression model.
Language: Jupyter Notebook - Size: 2.93 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0
Mikhail-Repkin/Yandex_Practikum_projects
Учебные проекты в рамках программы профессиональной переподготовки: Специалист по Data Science
Language: Jupyter Notebook - Size: 5.4 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0
iamzehan/kaggle_timeseries
Time Series Forecasting
Language: Jupyter Notebook - Size: 13.1 MB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0
kuzinkirill/yandex_ds_projects
Проекты, выполненные в ходе обучения в Яндекс.Практикум по профессии "Специалист по Data Science"
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aman9801/stock-price-prediction-using-arima
Stock Price Prediction using ARIMA
Language: Jupyter Notebook - Size: 644 KB - Last synced at: about 2 years ago - Pushed at: about 3 years ago - Stars: 1 - Forks: 1
MoinDalvs/Learn_Simple_Linear_Regression
Learn about Simple Linear Regression for Data Science
Language: Jupyter Notebook - Size: 745 KB - Last synced at: 3 months ago - Pushed at: about 3 years ago - Stars: 1 - Forks: 0
SerhatDerya/Tabular-Playground-Series
This repository contains solutions of monthly Tabular Playground Series in Kaggle.
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280220/Ironhack-Labs
Collection of laboratories I did during Ironhack's Data Analytics bootcamp.
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yashrajsingh11/Time_Series_Forecasting_SARIMA
Language: Jupyter Notebook - Size: 1.53 MB - Last synced at: 3 months ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 0
rainaa0277/House-Price-Prediction-using-Linear-Regression
For a real estate firm, building a house price prediction model based upon various factors. Problem - Regression | Algorithm used -Linear Regression using OLS
Language: Jupyter Notebook - Size: 4.03 MB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 0
kaispace30098/Sales-Prediction---Holt-Winters-Model
Tuning Trend/ Seasonality/ Error level from Exponential Smoothing model to make futrure forcast
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ashishyadav24092000/Regression1_hydrocarbon_O2
It gives the regression equation and model for a sample problem in which the percentage of hydrocarbon pre distillation determines the percentage of purity obtained or O2 obtained post distillation process.
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ashishyadav24092000/CAT_SCORE_ANALYSIS_FACTORIAL_EXPERIMENT
This problem concludes which factor is significantly effecting the CAT Score out of College type,program type,and interaction factor type for sample data. Here factorial Experiment design and Two Way Anova is used.
Language: Jupyter Notebook - Size: 7.55 MB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 0
rakibhhridoy/EasyWayDiveInto-DataScience
Data Science is not as easy as it seems at first. The most problem faced by new learner are lack of resource knowledge as well as confusion in using the various resources. I hope this repository will benefit confusion learner.
Language: Jupyter Notebook - Size: 5.89 MB - Last synced at: 22 days ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 2
ascii-monk123/Ford-Used-Car-Price-Prediction
Regression Analysis on Ford Used Car Price Dataset as a project
Language: Jupyter Notebook - Size: 402 KB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 0
paul-lindquist/king-county-home-sales
Used linear regression to build inferential and predictive machine learning models on the King County, WA housing dataset
Language: Jupyter Notebook - Size: 26.6 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 1
vaitybharati/P26.-Supervised-ML---Multiple-Linear-Regression---Cars-dataset
Supervised-ML---Multiple-Linear-Regression---Cars-dataset. Model MPG of a car based on other variables. EDA, Correlation Analysis, Model Building, Model Testing, Model Validation Techniques, Collinearity Problem Check, Residual Analysis, Model Deletion Diagnostics (checking Outliers or Influencers) Two Techniques : 1. Cook's Distance & 2. Leverage value, Improving the Model, Model - Re-build, Re-check and Re-improve - 2, Model - Re-build, Re-check and Re-improve - 3, Final Model, Model Predictions.
Language: Jupyter Notebook - Size: 507 KB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 1 - Forks: 0
vaitybharati/P25.-Supervised-ML---Simple-Linear-Regression---Waist-Circumference-Adipose-Tissue-Data
Supervised-ML---Simple-Linear-Regression---Waist-Circumference-Adipose-Tissue-Data. EDA and data visualization, Correlation Analysis, Model Building, Model Testing, Model Prediction.
Language: Jupyter Notebook - Size: 178 KB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 1 - Forks: 0
adinas94/King-Country-Regression
Regression analysis in statsmodels to help housing development company determine where to build properties, and what prices these properties should be set at to maximize profits.
Language: Jupyter Notebook - Size: 19.2 MB - Last synced at: almost 2 years ago - Pushed at: about 4 years ago - Stars: 1 - Forks: 0
vaitybharati/P19.-Hypothesis-Testing-2-Proportion-T-test-Students-Jobs-in-2-States-
Hypothesis-Testing-2-Proportion-T-test-Students-Jobs-in-2-States. Assume Null Hypothesis as Ho is p1-p2 = 0 i.e. p1 ≠ p2. Thus Alternate Hypthesis as Ha is p1 = p2. Explanation of bernoulli Binomial RV: np.random.binomial(n=1,p,size) Suppose you perform an experiment with two possible outcomes: either success or failure. Success happens with probability p, while failure happens with probability 1-p. A random variable that takes value 1 in case of success and 0 in case of failure is called a Bernoulli random variable. Here, n = 1, Because you need to check whether it is success or failure one time (Placement or not-placement) (1 trial) p = probability of success size = number of times you will check this (Ex: for 247 students each one time = 247) Explanation of Binomial RV: np.random.binomial(n=1,p,size) (Incase of not a Bernoulli RV, n = number of trials) For egs: check how many times you will get six if you roll a dice 10 times n=10, P=1/6 and size = repetition of experiment 'dice rolled 10 times', say repeated 18 times, then size=18. As (p_value=0.7255) > (α = 0.05); Accept Null Hypothesis i.e. p1 ≠ p2 There is significant differnce in population proportions of state1 and state2 who report that they have been placed immediately after education.
Language: Jupyter Notebook - Size: 176 KB - Last synced at: over 1 year ago - Pushed at: about 4 years ago - Stars: 1 - Forks: 0
krunal-nagda/Boom-Bikes-Case-Study---Linear-Regression
Modeling the demand for shared bikes with the available independent variables in the given dataset 'day'. It will be used by the management to understand how exactly the demands vary with different features. They can accordingly manipulate the business strategy to meet the demand levels and meet the customer's expectations. Further, the model will be a good way for management to understand the demand dynamics of a new market.
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cassnutt/Housing_price_predictions Fork of learn-co-curriculum/dsc-phase-2-project
This project used linear regression to predict the prices of homes for sale in King County Washington. The dataset contains over 21,500 listings and 21 features. A model was created with statsmodels that would explain 80% of the variance in price.
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andiosika/Multiple-linear-regression-for-predicting-home-prices
Using 21 categorical and numeric features in a multivariate linear regression to find that 79% of a home price can be positively affected by a combination of certain features like location, square feet, condition and age of the home.
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ruankie/stock-market-prediction
Forecasting accuracy comparison of various machine learning and statistical models on stock market price movements
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MagedMohamedTurk/Cars_price_ML
Exploring and predicting the price of cars based on their features
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vaitybharati/Forecasting_Model_Arima
Persistence/ Base model, ARIMA Hyperparameters, Grid search for p,d,q values, Build Model based on the optimized values, Combine train and test data and build final model
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alumik/time-series-decomposition
A practical example of time series decomposition
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SrajanKumarShukla/Apparent-Temperature-Prediction
It is a project made to predict the apparent temperature using linear regression.
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AbhishekKumar-0311/ML-BikeSharing-Demand-Prediction
This project tries to predict shared bike demand after the ongoing quarantine situation ends using multiple linear regression model.
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sam14032000/volatility_prediction_study
Testing a hybrid VAR+ML model for predicting stock market volatility
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AayushChaube/Superstore---Time_Series_Analysis
A Time Series Analysis and Forecasting, using ARIMA and Prophet models, on a superstore dataset.
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vaitybharati/Simple-linear-Reg-1
Simple-linear-Reg-1
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rakibhhridoy/ExploratoryDataAnalysis-Python
Exploratory data analysis is an approach to analyzing data sets to summarize their main characteristics, often with visual methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling or hypothesis testing task.
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javzapata/NYCOpenData
Data Science examples using NYC Open Data service requests
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Ashutosh27ind/multipleLinearRegressionHousingCaseStudy
Data Science Project :To use the data to optimize the sale prices of the properties based on important factors such as area, bedrooms, parking, etc.
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Ashutosh27ind/linearRegressionCarPricePredictionAssignment
Data Science Project: To build a multiple linear regression model for the prediction of car prices.
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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)
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rish-av/shm_machineLearning
Statistical Learning Models for Damage Detection in Civil Structures.
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