Does it provide a measure of accuracy for its predictions?

Yes, the skill generates predictions along with confidence intervals and can evaluate model performance using metrics like Mean Absolute Error (MAE) or Root Mean Squared Error (RMSE).

Can it handle missing data in the time series?

While the skill performs best with clean data, it uses Claude's analytical capabilities to identify gaps and can be used in conjunction with data cleaning scripts to prepare datasets for forecasting.

What industries benefit most from this skill?

It is highly effective for retail (sales forecasting), IT (traffic prediction), finance (trend analysis), and any sector reliant on time-dependent metrics.

Which forecasting models does this skill support?

The skill intelligently selects the best model based on data characteristics, typically utilizing proven statistical methods like ARIMA for stationary data or Prophet for data with strong seasonal patterns.

Time Series Forecaster

Name: Time Series Forecaster
Author: BbgnsurfTech

byBbgnsurfTech

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データサイエンスとML

Predicts future values and identifies patterns in historical time-dependent data using advanced statistical models.

概要

This skill empowers Claude to perform sophisticated time series forecasting by automating the end-to-end process of data analysis, model selection, and prediction generation. By analyzing historical datasets for underlying trends, seasonality, and autocorrelation, it identifies the most suitable forecasting models—such as ARIMA or Prophet—and generates actionable future projections with confidence intervals to support data-driven decision-making.

主な機能

Intelligent selection of statistical models like ARIMA and Prophet
Generation of future value predictions with confidence intervals
Comprehensive autocorrelation and data characteristic analysis
Automated detection of trends, seasonality, and patterns
Integration with Bash for custom data processing and modeling scripts
3 GitHub stars

ユースケース

Predicting website traffic or server load to optimize infrastructure planning
Forecasting quarterly sales and revenue based on historical monthly data
Analyzing stock price trends and financial metrics for market insights

概要

主な機能

Intelligent selection of statistical models like ARIMA and Prophet
Generation of future value predictions with confidence intervals
Comprehensive autocorrelation and data characteristic analysis
Automated detection of trends, seasonality, and patterns
Integration with Bash for custom data processing and modeling scripts
3 GitHub stars

ユースケース

Predicting website traffic or server load to optimize infrastructure planning
Forecasting quarterly sales and revenue based on historical monthly data
Analyzing stock price trends and financial metrics for market insights