mape

Electric Load forecasting for a year on hourly basis using 3 different techniques. - linear Regression, - ANN (Using Matlab nntool), -K-Nearest Neighbor. All 3 codes are present with an detailed report on each technique.

energy linear-regression forecasting artificial-neural-networks mape knearest-neighbor matlab-nntool

UpdatedJan 9, 2021
Jupyter Notebook

asim5800 /Retail-Sales-Prediction

Star4

Sales forecasting is an essential task for the management of a store. Machine learning can help us discover the factors that influence sales in a retail store and estimate the number of sales in the near future.

python sales machine-learning random-forest linear-regression regression retail mape

UpdatedSep 23, 2023
Jupyter Notebook

Edision-liu /Deep-Reinforcement-Learning-on-MAPE

Star3

Swarm intelligence aims at exploring the complicated relationships among multi-agents to stimulate co-evolution and the emergence of intelligent decision-making. Based on Multi-agent Particle Environment and deep Reinforcement learning method, we propose ...

reinforcement-learning deep-reinforcement-learning swarm-intelligence mape

UpdatedDec 17, 2022
Python

heydarimo /Stock-Market-Prediction

Star3

in this repository we intend to predict Google and Apple Stock Prices Using Long Short-Term Memory (LSTM) Model in Python. Long Short-Term Memory (LSTM) is one type of recurrent neural network which is used to learn order dependence in sequence prediction problems. Due to its capability of storing past information, LSTM is very useful in predict…

mse lstm gru stock-price-prediction rnn adagrad rmsprop adam-optimizer droupout mape

UpdatedAug 15, 2022
Jupyter Notebook

DharshanSR /MLP-Neural-Network

Star3

R code for exchange rate prediction using Multilayer Perceptron (MLP) models with various architectures and evaluation metrics

machine-learning r neural-network feature-extraction mlp rmse mae mape smape modal-evaluation

UpdatedMay 20, 2024
R

Meta-Apes /meta-ape-nft-contract

Star3

Meta Apes is the all encompassing reward token, staking platform, and NFT ecosystem. Holding MAPES tokens allow you to receive 7% rewards in any BEP20 token of your choosing.

meta contract solidity token nft smartcontract binance mape apes meta-apes

UpdatedMar 26, 2022
Solidity

YenLinWu /Daily_Work_of_Data_Science

Star2

資料科學的日常研究議題

python data-science machine-learning statistics regression-models kernel-density-estimation correlation-coefficient mae kendall-tau pearson-correlation overfitting classification-models homogeneity mape normality-test r-squared spearman-rank-correlation model-drift maape chatterjee-correlation

UpdatedMar 12, 2025
Jupyter Notebook

shubhammandhare10 /Analyzing-Forecasting-Stock-Prices

Star2

Forecasting time series data using ARIMA models. Used covariance matrix to find dependencies between stocks.

rstudio stock-price-prediction data-analysis covariance-matrix forecasting-models rmse time-series-analysis normalization-data correlation-matrices arima-forecasting minmaxscaling mape

UpdatedMay 7, 2022
R

stdlib-js /stats-incr-mmaape

Sponsor

Star2

Compute a moving arctangent mean absolute percentage error (MAAPE) incrementally.

nodejs javascript node statistics math incremental stdlib mathematics mean error stats avg node-js average abs accumulator absolute err mape maape

UpdatedMar 17, 2025
JavaScript

pavankethavath /Dominos---Predictive-Purchase-Order-System

Star1

This advanced forecasting tool leverages Prophet, ARIMA, SARIMA, and LSTM models to predict daily sales for 32 pizzas and 64 ingredients. With Prophet achieving the lowest MAPE, it ensures accurate demand forecasts, optimized inventory, and efficient purchase planning, reducing waste, preventing stockouts, and enhancing supply chain efficiency.

python machine-learning deep-learning time-series tensorflow numpy exploratory-data-analysis eda prediction pandas seaborn lstm forecasting matplotlib arima sarimax seasonality minmaxscaling mape

UpdatedNov 27, 2024
Jupyter Notebook

vaitybharati /Forecasting_Data_Driven_Models

Star1

Splitting data, Moving Average, Time series decomposition plot, ACF plots and PACF plots, Evaluation Metric MAPE, Simple Exponential Method, Holt method, Holts winter exponential smoothing with additive seasonality and additive trend, Holts winter exponential smoothing with multiplicative seasonality and additive trend, Final Model by combining …

python data-driven forecasting moving-average simple-exponential-smoothing holt time-series-decomposition mape acf-plots holts-winter

UpdatedFeb 8, 2021
Jupyter Notebook

Akashash01 /Akash_Linear-regression

Star1

This is an linear approach machine learning model used to predict the values of variable(dependent) based on other variables(independent).

python data-science machine-learning numpy linear-regression pandas supervised-learning autocorrelation multicollinearity heteroscedasticity mape anova-test

UpdatedOct 8, 2024
Python

bryce-bowles /tsf-richmond-bank

Star1

Using MS Excel and R, accurately forecasted total core deposit data from a Richmond Bank. The Holt’s Linear Exponential Smoothing had the overall lowest “Quick and Dirty” MAPE (1.2%), the lowest overall Maximum MAPE (3.49%), and consistently more accurate projections for each of the forecast horizons. Overall, the Unaided, Holts Linear Exponenti…

r excel regression-models exponential-smoothing time-series-forecasting mape holt-winters-forecasting