GitHub
td-train-test-split
Data splitting for model validation using TD_TrainTestSplit
Skills IA tools machine learning
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Catégories: tools machine learning
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GitHub
td-data-preparation
UAF-specific data preparation and validation for time series analysis
GitHub
td-onehot-encoding
Categorical variable encoding using TD_OneHotEncodingFit and Transform
GitHub
td-cross-validation
Time series specific cross-validation techniques for model validation
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td-linear-regression
Linear regression analysis for continuous target prediction
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td-simple-impute
Missing value imputation using TD_SimpleImputeFit
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td-tfidf
Term Frequency-Inverse Document Frequency for text analysis
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td-movavg-forecast
Moving average based forecasting for smoothed predictions
GitHub
td-arima
ARIMA modeling for time series forecasting
GitHub
td-naive-bayes
Naive Bayes classifier for probabilistic classification
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td-decision-tree
Decision tree classifier for categorical prediction and rule extraction
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td-convolution
Convolution operations for signal processing and filtering
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td-outlier-detection
Outlier detection and handling using TD_OutlierFit
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td-diff
Time series differencing for stationarity and trend removal
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td-arimaestimate
ARIMA parameter estimation for seasonal and non-seasonal AR, MA, ARMA, and ARIMA models
GitHub
td-decision-forest
Decision forest ensemble classifier for robust predictions
GitHub
td-portman
Ljung-Box portmanteau tests for model diagnostics and residual analysis
GitHub
td-logistic-regression
Logistic regression for binary and multinomial classification
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td-classification-evaluator
Classification model evaluation and metrics calculation
GitHub
td-random-forest
Random forest ensemble classifier for high-accuracy classification
GitHub
td-parameter-estimation
Advanced parameter estimation and optimization for UAF models
GitHub
td-column-transformer
Advanced column transformation and feature engineering
GitHub
td-scale-fit
Data scaling and normalization using TD_ScaleFit and TD_ScaleTransform
GitHub
td-acf
Auto-correlation analysis for time series dependency and pattern detection
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.