以邏輯迴歸分析影響航空公司客戶忠誠度的因素

Comprehensive daily Bitcoin (2014–2025) time-series analysis in R using tidy workflows, tsibble, and fable. Explores trends, volatility, and regimes, and benchmarks Naive, Drift, and ARIMA models—showing simple baselines often outperform complex methods.

This is the 2nd part of the machine learning of fibromyalgia data comparisons using the same 1st part work on means of samples' fold change values of healthy vs myofascial pain, but now compared with the medians of those fold change values and different parameter tuning for 50, 100, and 1000 bootstrapped samples from only 13 to predict class correctly in the means then in the medians, and try same number of folds as best bootstrap aggregating value for cross validation on means and medians separately. A few models returned 100% accuracy on only 3 test samples.

Analysis of NOAA's Storm Database regarding weather events causing the most injuries/deaths and economic damage to property/crops.