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teradata-labs

teradata-labs

72 Skills published on GitHub.

td-acf

Auto-correlation analysis for time series dependency and pattern detection

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Teradata ANOVA

Analysis of variance for comparing group means

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td-arima-forecast

ARIMA-based time series forecasting for trend and seasonal predictions

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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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Teradata AutoARIMA

Automated ARIMA model selection and forecasting

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td-change-point

Change point detection in time series for structural breaks

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Teradata Chi-Square Test

Chi-square test of independence for categorical variables

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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-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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Teradata F-Test

F-test for comparing variances between two groups

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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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Teradata HNSW Vector Search

Approximate nearest neighbor search using HNSW algorithm

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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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Teradata K-Nearest Neighbors Analytics

K-Nearest Neighbors for classification and regression

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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-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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Teradata ONNX Model Scoring

Score data using ONNX models (Bring Your Own Model)

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Teradata Ordinal Encoding Suite

Ordinal encoding for ordered categorical variables

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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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Teradata PMML Model Scoring

Score data using PMML models (Bring Your Own Model)

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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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Teradata ROC Curve Analysis

ROC curve and AUC analysis for binary classification evaluation

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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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Teradata Sentiment Extraction

Sentiment analysis for text documents and sentences

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td-sessionize

Session analysis and user journey tracking

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Teradata SHAP Explainability

SHAP values for model explainability and feature importance

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Teradata Silhouette Analysis

Silhouette coefficient for clustering quality evaluation

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