Nixtla / hierarchicalforecast
Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.
☆633Updated this week
Alternatives and similar repositories for hierarchicalforecast:
Users that are interested in hierarchicalforecast are comparing it to the libraries listed below
- Scalable machine 🤖 learning for time series forecasting.☆988Updated this week
- Calculates various features from time series data. Python implementation of the R package tsfeatures.☆396Updated 10 months ago
- Forecasting with Gradient Boosted Time Series Decomposition☆193Updated last year
- Transfer 🤗 Learning for Time Series Forecasting☆244Updated 3 months ago
- Hierarchical Time Series Forecasting with a familiar API☆224Updated last year
- The practitioner's forecasting library☆334Updated this week
- Predict time-series with one line of code.☆421Updated 5 months ago
- Automated Time Series Forecasting☆1,223Updated 2 weeks ago
- A python package for time series forecasting with scikit-learn estimators.☆161Updated 11 months ago
- An extension of LightGBM to probabilistic modelling☆295Updated 9 months ago
- Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Created by Ra…☆749Updated 7 months ago
- Datasets for time series forecasting☆89Updated last month
- Time should be taken seer-iously☆314Updated 2 years ago
- Flexible time series feature extraction & processing☆413Updated 6 months ago
- Quantile Regression Forests compatible with scikit-learn.☆227Updated this week
- Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.☆632Updated 2 months ago
- This repository contains the implementations related to the experiments of a set of publicly available datasets that are used in the time…☆224Updated 2 years ago
- Helper functions to plot, evaluate, preprocess and engineer features for forecasting☆56Updated 2 weeks ago
- Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.☆1,084Updated 8 months ago
- A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.☆610Updated last year
- A unified framework for tabular probabilistic regression, time-to-event prediction, and probability distributions in python☆260Updated this week
- N-BEATS is a neural-network based model for univariate timeseries forecasting. N-BEATS is a ServiceNow Research project that was started …☆534Updated 2 years ago
- A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.☆1,350Updated this week
- A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.☆574Updated 9 months ago
- Data, Benchmarks, and methods submitted to the M5 forecasting competition☆603Updated last year
- A Python package for causal inference in quasi-experimental settings☆958Updated this week
- An extension of XGBoost to probabilistic modelling☆586Updated 8 months ago
- catch22: CAnonical Time-series CHaracteristics☆392Updated this week
- Python package for conformal prediction☆483Updated 6 months ago
- ☆157Updated 3 years ago