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mape
Here are 31 public repositories matching this topic...
Distributed and decentralized MAPE-K loops framework
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Dec 20, 2022 - Python
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
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Jan 9, 2021 - Jupyter Notebook
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.
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Sep 23, 2023 - Jupyter Notebook
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 ...
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Dec 17, 2022 - Python
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…
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Aug 15, 2022 - Jupyter Notebook
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
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May 7, 2022 - R
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
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Dec 1, 2024 - JavaScript
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
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Nov 27, 2024 - Jupyter Notebook
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
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Oct 8, 2024 - Python
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
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Jan 21, 2022 - R
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
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Feb 8, 2021 - Jupyter Notebook
deep-learning stock-market lstm-model rmse time-series-analysis exponential-moving-average simple-moving-average mape
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May 8, 2022 - Jupyter Notebook
R code for exchange rate prediction using Multilayer Perceptron (MLP) models with various architectures and evaluation metrics
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May 20, 2024 - R
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
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Dec 18, 2024 - Jupyter Notebook
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Oct 16, 2021 - HTML
Compute the mean absolute percentage error (MAPE) incrementally.
nodejs javascript node statistics math percentage stdlib mathematics mean error stats avg node-js average percent abs absolute err mape arithmetic-mean
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Dec 1, 2024 - JavaScript
Compute a moving mean absolute percentage error (MAPE) incrementally.
nodejs javascript node statistics math percentage incremental stdlib mathematics mean error stats avg node-js average percent abs absolute err mape
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Updated
Dec 1, 2024 - JavaScript
Compute the mean arctangent absolute percentage error (MAAPE) incrementally.
nodejs javascript node statistics math stdlib mathematics mean error stats avg node-js average difference deviation abs absolute err mape arithmetic-mean
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Updated
Dec 1, 2024 - JavaScript
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