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Claude Skills by LeoLin990405
github.com/LeoLin990405307 skills2 installs264 views
- R Ml AnomalyR anomaly detection. Use for outlier detection, breakpoint detection with AnomalyDetection, anomalize, and changepoint.Votes: 0GitHub stars: 5
- AnomalizeR anomalize package for tidy anomaly detection. Use for detecting anomalies in time series with tidyverse workflow.Votes: 0GitHub stars: 5
- R Ml BoostingR gradient boosting packages. Use for xgboost, lightgbm, gbm, and catboost.Votes: 0GitHub stars: 5
- LightgbmR lightgbm package for gradient boosting. Use for fast, distributed, high-performance gradient boosting.Votes: 0GitHub stars: 5
- XgboostR xgboost package for gradient boosting. Use for high-performance classification, regression, and ranking.Votes: 0GitHub stars: 5
- R Ml ClusteringR packages for clustering analysis. Use for k-means, hierarchical clustering, and other clustering methods.Votes: 0GitHub stars: 5
- ClusterR cluster package for clustering algorithms. Use for PAM, CLARA, AGNES, DIANA, and other clustering methods.Votes: 0GitHub stars: 5
- DbscanR dbscan package for density-based clustering. Use for DBSCAN, OPTICS, and HDBSCAN clustering.Votes: 0GitHub stars: 5
- FactoextraR factoextra package for cluster visualization. Use for visualizing clustering results and PCA.Votes: 0GitHub stars: 5
- MclustR mclust package for model-based clustering. Use for Gaussian mixture models and model-based clustering.Votes: 0GitHub stars: 5
- R Ml DeeplearningR deep learning with torch, keras, tensorflow. Use for neural networks, CNNs, RNNs, and GPU acceleration.Votes: 0GitHub stars: 5
- KerasR keras package for deep learning. Use for neural networks with TensorFlow backend.Votes: 0GitHub stars: 5
- TorchR torch package for deep learning. Use for PyTorch-style neural networks in R.Votes: 0GitHub stars: 5
- RtsneR Rtsne package for t-SNE. Use for t-distributed stochastic neighbor embedding visualization.Votes: 0GitHub stars: 5
- R Ml DimensionalityR packages for dimensionality reduction. Use for PCA, t-SNE, UMAP, and other dimension reduction methods.Votes: 0GitHub stars: 5
- IrlbaR irlba package for fast SVD/PCA. Use for truncated SVD and PCA on large matrices.Votes: 0GitHub stars: 5
- UmapR umap package for UMAP. Use for Uniform Manifold Approximation and Projection visualization.Votes: 0GitHub stars: 5
- BorutaR Boruta package for feature selection. Use for all-relevant feature selection using random forest.Votes: 0GitHub stars: 5
- R Ml FrameworksR machine learning frameworks. Use for unified ML workflows with tidymodels, caret, mlr3, and h2o.Votes: 0GitHub stars: 5
- ArulesR arules package for association rules. Use for mining frequent itemsets and association rules.Votes: 0GitHub stars: 5
- CaretR caret package for machine learning. Use for training, tuning, and evaluating classification and regression models.Votes: 0GitHub stars: 5
- E1071R e1071 package for SVM and misc functions. Use for support vector machines, naive Bayes, and clustering.Votes: 0GitHub stars: 5
- GbmR gbm package for gradient boosting. Use for gradient boosted regression and classification models.Votes: 0GitHub stars: 5
- H2oR h2o package for scalable ML. Use for distributed machine learning with AutoML and deep learning.Votes: 0GitHub stars: 5
- KernlabR kernlab package for kernel methods. Use for support vector machines and kernel-based learning.Votes: 0GitHub stars: 5
- Lme4R lme4 package for mixed-effects models. Use for fitting linear and generalized linear mixed-effects models.Votes: 0GitHub stars: 5
- Mlr3R mlr3 package for machine learning. Use for modern ML framework with pipelines, tuning, and benchmarking.Votes: 0GitHub stars: 5
- NlmeR nlme package for mixed-effects models. Use for linear and nonlinear mixed-effects models with correlation structures.Votes: 0GitHub stars: 5
- RandomForestR randomForest package for random forest models. Use for classification and regression with ensemble of decision trees.Votes: 0GitHub stars: 5
- RpartR rpart package for decision trees. Use for recursive partitioning classification and regression trees.Votes: 0GitHub stars: 5
- TidymodelsR tidymodels package for machine learning. Use for modeling workflows with recipes, parsnip, tune, and yardstick.Votes: 0GitHub stars: 5
- DALEXR DALEX package for model explanations. Use for explaining complex machine learning models.Votes: 0GitHub stars: 5
- R Ml InterpretabilityR packages for ML interpretability. Use for explaining and interpreting machine learning models.Votes: 0GitHub stars: 5
- ImlR iml package for interpretable ML. Use for model-agnostic interpretability methods.Votes: 0GitHub stars: 5
- LimeR lime package for local explanations. Use for explaining individual predictions with local interpretable models.Votes: 0GitHub stars: 5
- VipR vip package for variable importance. Use for computing and visualizing variable importance scores.Votes: 0GitHub stars: 5
- R Ml RegularizationR regularized regression. Use for lasso, ridge, elastic-net with glmnet, and penalized regression.Votes: 0GitHub stars: 5
- GlmnetR glmnet package for regularized regression. Use for lasso, ridge, and elastic-net regularization.Votes: 0GitHub stars: 5
- R Ml SurvivalR survival analysis. Use for Kaplan-Meier, Cox regression, survival curves with survival and survminer.Votes: 0GitHub stars: 5
- SurvivalR survival package for survival analysis. Use for Kaplan-Meier curves, Cox regression, and time-to-event analysis.Votes: 0GitHub stars: 5
- SurvminerR survminer package for survival visualization. Use for publication-ready Kaplan-Meier plots and forest plots.Votes: 0GitHub stars: 5
- R Ml TimeseriesR time series forecasting. Use for prophet, forecast, fable, ARIMA, and exponential smoothing.Votes: 0GitHub stars: 5
- FableR fable package for tidy time series forecasting. Use for modern forecasting with tsibble integration.Votes: 0GitHub stars: 5
- ForecastR forecast package for time series forecasting. Use for ARIMA, ETS, and automatic forecasting.Votes: 0GitHub stars: 5
- ProphetR prophet package for time series forecasting. Use for forecasting with seasonality, holidays, and trend changes.Votes: 0GitHub stars: 5
- TsibbleR tsibble package for tidy time series. Use for temporal data structures with tidyverse integration.Votes: 0GitHub stars: 5
- R Ml TreesR tree-based models. Use for random forests, decision trees, and ensemble methods with ranger, randomForest, rpart.Votes: 0GitHub stars: 5
- RangerR ranger package for random forests. Use for fast implementation of random forests for classification and regression.Votes: 0GitHub stars: 5
- R NetworkR network analysis packages. Use for graph analysis, social network analysis, network visualization, and community detection.Votes: 0GitHub stars: 5
- R Network AnalysisR network analysis with igraph, sna. Use for centrality, community detection, and network metrics.Votes: 0GitHub stars: 5