mean-absolute-error

There are 2 repositories under mean-absolute-error topic.

zzhanghub / eval-co-sod
PyTorch-Based Evaluation Tool for Co-Saliency Detection
co-saliency salient-object-detection pytorch evaluation f-measure e-measure s-measure auc pr-curve roc-curve average-precision mae mean-absolute-error python
Language:Python 99
XinshaoAmosWang / Improving-Mean-Absolute-Error-against-CCE
Mean Absolute Error Does Not Treat Examples Equally and Gradient Magnitude’s Variance Matters
data-fitting reweighting-examples label-noise mean-absolute-error category-cross-entropy outliers
Language:Shell 30
sushantdhumak / 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.
arima-model augmented auto-arima dickey-fuller-test differencing exploratory-data-analysis grid-search industrial-automation mean-absolute-error mean-absolute-percentage-error mean-square-error stationarity
Language:Jupyter Notebook 3
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
autoregressive-integrated-moving-average-arima bilinear-interpolation linear-regression mean-absolute-error mean-square-error root-mean-square-error
Language:Jupyter Notebook 2
rjnp2 / deep_learning_from_scratch
deep-learning cupy gpu cnn dense conv mean-absolute-error rmsprop
Language:Python 2
SCIFER99 / Building-Machine-Learning-Models-with-Python
Build Linear Regression and Mean Absolute Error Models with Python for Machine Learning
ai machine-learning statistical-analysis statistical-learning linear-regression mean-absolute-error
Language:Jupyter Notebook 2
aaaastark / Intrusion-Detection-System-MQTT-Enabled-IoT
Intrusion Detection System for MQTT Enabled IoT.
artifical-neural-network binary-classification classification-report data-processing data-visualization deep-learning feature-extraction intrusion-detection-system keras-tensorflow mean-absolute-error mean-squared-error mqtt mqtt-protocol mqtt-server multi-class-classification r2-score root-mean-square-error sklearn
1
BradyFisher / Housing-Prices-Machine-Learning-Project
This is a project where I use the Random Forest Regression and XGBoost Machine Learning Techniques to held predict the Sales Price of Houses..
jupyter-notebook machine-learning mean-absolute-error one-hot-encoding random-forest-regression simpleimputer train-test-split validation xgboost-regression
Language:Jupyter Notebook 1
BradyFisher / Machine-Learning-Titanic-Project
This is a project where use the Random Forest Classifier and XGBoost Machine Learning Techniques to held predict what passengers survived the sinking of the Titanic.
machine-learning mean-absolute-error one-hot-encoding random-forest-classifier simpleimputer train-test-split validation xgboost-classifier jupyter-notebook
Language:Jupyter Notebook 1
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.
apache-beam dataframes glob kmeans-clustering matplotlib-pyplot mean-absolute-error mean-square-error numpy os pandas pipelines scipy-stats seaborn silhouette-score sklearn sklearn-datasets standardscaler
Language:Python 1
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`.
curses kaggle linear-regression matplotlib-pyplot mean-absolute-error mean-square-error numpy pandas pathlib python scikit-learn train-test-split
Language:Python 1
guilhermedom / perceptron-regression-ice-cream-per-temp
Perceptron regressing revenue for an ice cream stand according to temperature.
linear-regression linear-regression-assumptions mean-absolute-error neural-network-regression ordinary-least-squares-regression perceptron python r2-score scikit-learn simple-linear-regression tensorflow revenue-regression chi-squared-distribution normal-distribution qq-plot
Language:Jupyter Notebook 1
gurol / BenchMetricsProb
BenchMetrics Prob: Benchmarking of probabilistic error performance evaluation instruments for binary-classification problems
benchmarking machine-learning metrics performance-measures performance-metrics supervised-learning binary-classification classification confusion-matrix performance-evaluation robustness logloss root-mean-square-error root-mean-squared-error-metric mean-absolute-error
1
jong26 / rainfall_prediction_ml
This project used various machine learning algorithms to predict rainfall.
decision-trees f1-score jaccard-similarity knn linear-regression logistic-regression mean-absolute-error mean-squared-error r2-score svm
Language:Jupyter Notebook 1
MrRaghav / airbnb-in-berlin-2020
A data mining project to analyse Airbnb's data of Berlin for the year 2020 using KDD
airbnb berlin data-mining kdd linear-regression knn decision-trees random-forest rmse r2-score mean-absolute-error seasonality insideairbnb word-cloud amenities neighborhood outliers data-processing missing-data large-dataset
Language:Jupyter Notebook 1
mustaffa-hussain / Performance-Metric
This Repository contains scratch implementations of the famous metrics used to evaluate machine learning models.
auc accuracy f1-score confusion-matrix mse mean-square-error mean-absolute-error r2-score precision
Language:Jupyter Notebook 1
nikhilt1998 / DrivenData-DengAI-Predicting-Disease-Spread
DengAI: Disease spread prediction(DrivenData Challenge)
machine-learning neural-network regression regression-models datapreprocessing mean-absolute-error competition drivendata timeseries-analysis
Language:Jupyter Notebook 1
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.
linear-regression mean-absolute-error pandas-library python-library seaborn-pairplot train-test-split train-test-using-sklearn
Language:Jupyter Notebook 1
Ashwin0229 / Collaborative-Filtering-K-nearest-neighbors-and-SVM
Using Collaborative Filtering predicting Movie Rating and K-nearest Neighbours & SVM algorithms for Number ClassificationNumber Classification
collaborative-filtering f1-score gridsearchcv k-nearest-neighbor-classifier linearsvc-model machine-learning-algorithms mean-absolute-error mean-square-error precision-recall python3 sklearn-library support-vector-machine svc
Language:Python 0
gkrusta / ft_linear_regression
A program that using machine learning algorithm can predict a price of a car based on it's mileage.
42 42born2code 42malaga gradient-descent ia linear-regression machine-learning mean-absolute-error python z-score-normalization
Language:Python 0
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.
bank decisiontreeclassifier f1-score matplotlib-pyplot mean-absolute-error mean-squared-error numpy pandas python3 r2-score randomforrestclassifier roc-auc-score scipy-stats seaborn sklearn
Language:Jupyter Notebook 0
LucasMLago / COVID-19-Healthy-Diet
A study about Regression algorithms
covid-19 healthy-diet mean-absolute-error mean-square-error probability-plot regression residual-plot
Language:Jupyter Notebook 0
maheera421 / Bulldozer-Price-Prediction-Model
Prediction of the auction prices of bulldozers using historical data.
datetime-formatters feature-importance hyperparameter-tuning imputation mean-absolute-error mean-squared-log-error parsing preprocessing random-forest-regressor randomizedsearchcv seaborn-plots
Language:Jupyter Notebook 0
maheera421 / California-Housing-Price-Prediction-Model
A regression model to predict housing prices based on various features.
grid-search-cross-validation mean-absolute-error mean-squared-error r2 random-forest-regressor random-search-algorithm test-scores train-test-split visulaization
Language:Jupyter Notebook 0
maheera421 / Car-Price-Prediction-Model
A machine learning project that predicts car prices based on a dataset.
column-transformer cross-validation-score feature-encoding feature-engineering imputation mean-absolute-error mean-squared-error one-hot-encoding r2-score random-forest-regressor simple-imputer
Language:Jupyter Notebook 0
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.
exploratory-data-analysis linear-regression linear-regression-assumptions mean-absolute-error mean-square-error model-performance r2-score
Language:Jupyter Notebook 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.
data-science decision-trees knn-algorithm linear-regression logistic-regression machine-learning mean-absolute-error mini-project svm
Language:Jupyter Notebook 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.
linear-regression mean-absolute-error mean-square-error residuals
Language:Jupyter Notebook
GMeghana19 / solar-power-output
Solar power prediction using liner regression
exploratory-data-analysis linear-regression mean-absolute-error predictive-modeling preprocessing-data visualizing-data predictingsolarpoweroutput
Language:Jupyter Notebook
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.
data-visualization decision-tree-regression grid-search-cv lasso-regression linear-regression matplotlib mean-absolute-error mean-squared-error numpy python3 r2-score random-forest-regression randomized-search-cross-validation ridge-regression seaborn sklearn spotify standardscaler
Language:Jupyter Notebook
Jiya-Patel-JP / Solar-Power-Prediction
Predicting solar power generation using Linear Regression
decision-tree linear-regression machine-learning mean-absolute-error r-squared random-forest solar-energy data jupyter-notebook matplotlib numpy pandas python scikit-learn seaborn
Language:Jupyter Notebook
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.
decision-tree grid-search-cv imputation linear-regression matplotlib mean-absolute-error numpy pandas preprocessing principal-component-analysis python3 random-forest scikit-learn seaborn lasso-regression ridge-regression feature-importance jupyter-notebook
Language:Jupyter Notebook
MylieMudaliyar / Feature-Engineering-Techiques-on-House-Values
The feature engineering techniques discussed are - dimensionality reduction(pca), scaling(standard scaler, normalizer, minmaxscaler), categorical encoding(one hot/dummy), binning, clustering, feature selection. These are techniques performed on a dataset consisting of Californian House Prices.
binning categorical-encoding dimensionality-reduction feature-engineering kmeans-clustering linear-regression mean-absolute-error minmaxscaler normalizer one-hot-encoding pca python random-forest-regressor standardscaler
Language:Jupyter Notebook
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
linear-regression machine-learning mean-absolute-error
Language:Jupyter Notebook
Vivek-Tate / WildTrack
WildTrack – Forecasting mountain wildlife populations using machine learning and time series analysis with ecological and satellite data.
arima-forecasting linear-regression lstm-model machine-learning matplotlib mean-absolute-error numpy pandas population-prediction python root-mean-square-error scikit-learn time-series-analysis
Language:Jupyter Notebook
Wb-az / MLib-PySpark-SoundLevel-Prediction
Creates a ML Pipeline leveraging PySpark SQL and PySpark MLib to predict sound level
correlation-analysis data-engineering-pipeline data-science grid-search mean-absolute-error mean-square-error metrics multivariate-regression nasa pyspark pyspark-mllib pyspark-sql python r-squared regressor rmse sound-processing
Language:Jupyter Notebook

mean-absolute-error

zzhanghub / eval-co-sod

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

sushantdhumak / ARIMA-for-Industrial-Production

AloRay / GAS-PRICE-FORECASTING

rjnp2 / deep_learning_from_scratch

SCIFER99 / Building-Machine-Learning-Models-with-Python

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

BradyFisher / Housing-Prices-Machine-Learning-Project

BradyFisher / Machine-Learning-Titanic-Project

CamilaJaviera91 / apache-beam-pipeline-first-approach

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

guilhermedom / perceptron-regression-ice-cream-per-temp

gurol / BenchMetricsProb

jong26 / rainfall_prediction_ml

MrRaghav / airbnb-in-berlin-2020

mustaffa-hussain / Performance-Metric

nikhilt1998 / DrivenData-DengAI-Predicting-Disease-Spread

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

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

gkrusta / ft_linear_regression

GunturWibawa / BetaBankChurnAnalysis

LucasMLago / COVID-19-Healthy-Diet

maheera421 / Bulldozer-Price-Prediction-Model

maheera421 / California-Housing-Price-Prediction-Model

maheera421 / Car-Price-Prediction-Model

manjugovindarajan / ReCell-Supervised-Learning-

ns-nexus / Rain-Prediction-in-Australia

EmamulHossen / LinearRegression

GMeghana19 / solar-power-output

GunturWibawa / SpotifyPopularityProbe

Jiya-Patel-JP / Solar-Power-Prediction

Lefteris-Souflas / Modern-Slavery-Analysis

MylieMudaliyar / Feature-Engineering-Techiques-on-House-Values

nnamanx / olympic-games

Vivek-Tate / WildTrack

Wb-az / MLib-PySpark-SoundLevel-Prediction