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teradata-labs

teradata-labs

63 Skills published on GitHub.

td-acf

Auto-correlation analysis for time series dependency and pattern detection

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td-arima-forecast

ARIMA-based time series forecasting for trend and seasonal predictions

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td-arima

ARIMA modeling for time series forecasting

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td-arimaestimate

ARIMA parameter estimation for seasonal and non-seasonal AR, MA, ARMA, and ARIMA models

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td-attribution

Marketing attribution modeling and analysis

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td-change-point

Change point detection in time series for structural breaks

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td-classification-evaluator

Classification model evaluation and metrics calculation

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td-column-transformer

Advanced column transformation and feature engineering

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td-convolution

Convolution operations for signal processing and filtering

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td-correlation

Signal correlation analysis for similarity and delay detection

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td-cross-validation

Time series specific cross-validation techniques for model validation

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td-data-preparation

UAF-specific data preparation and validation for time series analysis

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td-data-profiling

Comprehensive data profiling and quality assessment using Teradata ClearScape Analytics descriptive statistics functions

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td-decision-forest

Decision forest ensemble classifier for robust predictions

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td-decision-tree

Decision tree classifier for categorical prediction and rule extraction

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td-detrend

Signal detrending for baseline correction and trend removal

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td-dfft

Fourier transformation for frequency domain analysis

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td-diff

Time series differencing for stationarity and trend removal

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td-fft

Fast Fourier Transform for frequency domain analysis and spectral decomposition

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td-filter

Digital filtering for noise reduction and signal enhancement

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td-glm

Comprehensive Generalized Linear Model analytics for regression and classification

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td-hierarchical-clustering

Hierarchical clustering for nested data grouping

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td-ifft

Inverse Fast Fourier Transform for time domain reconstruction

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td-kmeans

K-means clustering for customer segmentation and data grouping

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td-linear-regression

Linear regression analysis for continuous target prediction

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td-logistic-regression

Logistic regression for binary and multinomial classification

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td-model-selection

Automated model selection and comparison for optimal forecasting

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td-movavg-forecast

Moving average based forecasting for smoothed predictions

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td-naive-bayes

Naive Bayes classifier for probabilistic classification

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td-ngram-splitter

N-gram generation for text preprocessing

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td-npath

Path analysis for sequential event patterns

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td-onehot-encoding

Categorical variable encoding using TD_OneHotEncodingFit and Transform

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td-outlier-detection

Outlier detection and handling using TD_OutlierFit

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td-pacf

Partial auto-correlation analysis for direct lag relationships

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td-parameter-estimation

Advanced parameter estimation and optimization for UAF models

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td-plot

Time series visualization and diagnostic plotting utilities

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td-portman

Ljung-Box portmanteau tests for model diagnostics and residual analysis

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td-powerspec

Power spectrum analysis for frequency domain insights and periodicity detection

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td-random-forest

Random forest ensemble classifier for high-accuracy classification

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td-regression-evaluator

Comprehensive regression model evaluation using TD_RegressionEvaluator

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td-resample

Signal resampling and interpolation for rate conversion

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td-scale-fit

Data scaling and normalization using TD_ScaleFit and TD_ScaleTransform

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td-seasonal-decompose

Seasonal pattern decomposition and analysis

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td-sessionize

Session analysis and user journey tracking

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td-simple-impute

Missing value imputation using TD_SimpleImputeFit

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td-smoothing

Signal smoothing and noise reduction techniques

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td-spectral-density

Power spectral density estimation for frequency content analysis

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td-stationarity-test

Statistical tests for time series stationarity (ADF, KPSS, PP tests)

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td-svm

Support Vector Machine for linear and non-linear classification

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td-tfidf

Term Frequency-Inverse Document Frequency for text analysis

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teradata-labs | Agent Skills