GitHub topics: mean-absolute-error

Repositories

Wb-az/MLib-PySpark-SoundLevel-Prediction

Creates a ML Pipeline leveraging PySpark SQL and PySpark MLib to predict sound level

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CamilaJaviera91/apache-beam-pipeline-first-approach

This code demonstrates how to integrate Apache Beam with scikit-learn datasets and perform simple data transformations. It loads the Linnerud dataset from scikit-learn, converts it into a Pandas DataFrame for easier manipulation.

Language: Python - Size: 608 KB - Last synced at: 28 days ago - Pushed at: 3 months ago - Stars: 1 - Forks: 0

CamilaJaviera91/Prediction-of-Housing-Prices-Using-Linear-Regression

This project provides tools to search for datasets on Kaggle, download and preprocess them, and perform predictions using a Linear Regression model. It includes interactive text-based user interfaces built with `curses`.

Language: Python - Size: 397 KB - Last synced at: 9 days ago - Pushed at: 6 months ago - Stars: 1 - Forks: 0

GMeghana19/solar-power-output

Solar power prediction using liner regression

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sushant1827/ARIMA-for-Industrial-Production

Explains how to use ARIMA model to forecast future production units, enabling informed decision-making and planning in the electric and gas utilities sector.

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aaaastark/Intrusion-Detection-System-MQTT-Enabled-IoT

Intrusion Detection System for MQTT Enabled IoT.

Size: 1.55 MB - Last synced at: 3 months ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

maheera421/Bulldozer-Price-Prediction-Model

Prediction of the auction prices of bulldozers using historical data.

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maheera421/Car-Price-Prediction-Model

A machine learning project that predicts car prices based on a dataset.

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manjugovindarajan/ReCell-Supervised-Learning-

Analyze used devices dataset, build a model to develop a dynamic pricing strategy for used/refurbished devices, identify factors that significantly influence price.

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LucasMLago/COVID-19-Healthy-Diet

A study about Regression algorithms

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Vivek-Tate/Population-Forecast-Prediction

Population Prediction forecasts the Haggis population on a mountain. Ecologists have recorded the population over five years and have satellite estimates. The goal is to predict the true population 12 months ahead using machine learning and time series analysis techniques. This project is for the COM6509 - Machine Learning and Adaptive Intelligence

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AloRay/GAS-PRICE-FORECASTING

This repository utilizes time series analysis to predict natural gas prices, aiding informed decisions in the energy market. Through meticulous data preprocessing, visualization, and ARIMA modeling, it provides accurate forecasts. With regression and interpolation techniques, it offers deeper insights for stakeholders, enabling proactive strategies

Language: Jupyter Notebook - Size: 430 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0

ns-nexus/Rain-Prediction-in-Australia

We are going to use the different classification algorithms to create a model to predict rain in Australia. This project was done as a part of the Honors portion of the IBM Machine Learning Course on Coursera.

Language: Jupyter Notebook - Size: 135 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

zzhanghub/eval-co-sod

PyTorch-Based Evaluation Tool for Co-Saliency Detection

Language: Python - Size: 65.4 KB - Last synced at: about 1 year ago - Pushed at: over 4 years ago - Stars: 92 - Forks: 28

Lefteris-Souflas/Modern-Slavery-Analysis

Jupyter notebook using machine learning techniques to explore the complex drivers of modern slavery. Models from a research paper are replicated and evaluated . Actions also include filling missing data, training regression models, and analyzing feature importance.

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nnamanx/olympic-games

I use data from historical Olympic games and try to predict how many medals a country will win based on historical and current data

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Ashwin0229/Collaborative-Filtering-K-nearest-neighbors-and-SVM

Using Collaborative Filtering predicting Movie Rating and K-nearest Neighbours & SVM algorithms for Number ClassificationNumber Classification

Language: Python - Size: 95.7 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

EmamulHossen/LinearRegression

Linear regression is also a type of machine-learning algorithm more specifically a supervised machine-learning algorithm that learns from the labeled datasets and maps the data points to the most optimized linear functions.

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GunturWibawa/SpotifyPopularityProbe

In the digital music era, understanding artist popularity on Spotify is vital. This project taps into Spotify's data, analyzing key factors driving artist prominence. Through our insights, we illuminate what sets successful artists apart in this dynamic platform.

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mustaffa-hussain/Performance-Metric

This Repository contains scratch implementations of the famous metrics used to evaluate machine learning models.

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GunturWibawa/BetaBankChurnAnalysis

Beta Bank is losing customers monthly. Employees want to focus on client retention. As a Data Scientist, I created a model to predict the chance of a customer leaving, based on past behavior and contract terminations.

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iamkirankumaryadav/Regression

Regression - Bulldozer Sales Price - Kaggle Competition

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gurol/BenchMetricsProb

BenchMetrics Prob: Benchmarking of probabilistic error performance evaluation instruments for binary-classification problems

Size: 690 KB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0

LorenzoRottigni/ML-diabets

Machine Learning course of Piero Savastano 1: LinearRegression, mean_absolute_error, train_test_split

Language: Python - Size: 1000 Bytes - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

XinshaoAmosWang/Improving-Mean-Absolute-Error-against-CCE

Mean Absolute Error Does Not Treat Examples Equally and Gradient Magnitude’s Variance Matters

Language: Shell - Size: 45.1 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 29 - Forks: 3

Thakursiddhesh/Regression-Model-to-Predict-Cement-Compressive-Strength

Different modeling techniques like multiple linear regression and random forest, etc. will be used for predicting the cement compressive strength. A comparative analysis will be performed to identify the best model for our prediction in terms of accuracy.

Language: Jupyter Notebook - Size: 604 KB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

Related Keywords

mean-absolute-error 36 linear-regression 16 mean-square-error 13 r2-score 10 machine-learning 8 python 8 numpy 7 sklearn 6 pandas 6 python3 5 matplotlib-pyplot 4 root-mean-square-error 4 mean-squared-error 4 matplotlib 4 seaborn 4 scikit-learn 4 deep-learning 3 exploratory-data-analysis 3 f1-score 3 imputation 3 ridge-regression 3 cross-validation 2 mean-squared-log-error 2 train-test-split 2 root-mean-squared-error-metric 2 mae 2 feature-importance 2 auc 2 binary-classification 2 data-processing 2 data-visualization 2 decision-trees 2 outliers 2 linear-regression-assumptions 2 tensorflow 2 data-science 2 grid-search 2 metrics 2 neural-network-regression 2 neural-network 2 confusion-matrix 2 mse 2 regression 2 rmse 2 seaborn-plots 2 randomizedsearchcv 2 random-forest 2 random-forest-regressor 2 scipy-stats 2 lasso-regression 2 preprocessing 2 standardscaler 2 grid-search-cv 2 bicycle-sharing 1 seaborn-pairplot 1 python-library 1 pandas-library 1 reweighting-examples 1 non-linear-regression 1 train-test-using-sklearn 1 correlation-analysis 1 random-forest-regression 1 randomized-search-cross-validation 1 spotify 1 accuracy 1 precision 1 bank 1 decisiontreeclassifier 1 randomforrestclassifier 1 roc-auc-score 1 bulldozer 1 bulldozer-sales-price 1 randomforestregressor 1 benchmarking 1 classification 1 logloss 1 performance-evaluation 1 performance-measures 1 performance-metrics 1 robustness 1 supervised-learning 1 category-cross-entropy 1 data-fitting 1 label-noise 1 chi-squared-distribution 1 elastic-net 1 lasso 1 lasso-regression-model 1 airbnb 1 amenities 1 berlin 1 data-mining 1 insideairbnb 1 kdd 1 knn 1 large-dataset 1 missing-data 1 neighborhood 1 seasonality 1 word-cloud 1