Data Science Vocabulary

Creating new input variables from raw data

“Feature engineering extracted meaningful signals from the timestamp data.”

Reducing the number of variables while preserving information

“Dimensionality reduction made the dataset manageable for visualization.”

Evaluating models by training on subsets and testing on the rest

“Cross-validation revealed the model's true generalization performance.”

The proportion of positive predictions that are correct

“High precision means few false positives in our spam detection.”

The proportion of actual positives correctly identified

“High recall ensures we catch most fraudulent transactions.”

The harmonic mean of precision and recall

“The F1 score balances precision and recall into a single metric.”

A graph showing classifier performance at various thresholds

“The ROC curve demonstrated excellent discrimination between classes.”

Area Under the Curve, measuring overall model performance

“An AUC of 0.95 indicates excellent predictive ability.”

A table showing prediction results versus actual values

“The confusion matrix revealed the model confused cats with dogs.”

The balance between underfitting and overfitting

“Understanding the bias-variance tradeoff guides model complexity decisions.”

Techniques to prevent overfitting by penalizing complexity

“Regularization prevented the model from memorizing training data.”

Scaling data to a standard range

“Normalization ensured all features contributed equally to the model.”

Filling in missing data values

“Mean imputation replaced missing values with column averages.”

Identifying data points that differ significantly from others

“Outlier detection flagged suspicious transactions for review.”

Grouping similar data points together

“Clustering revealed three distinct customer segments.”

Predicting which category a data point belongs to

“Classification determines whether an email is spam or legitimate.”

Predicting a continuous numerical value

“Regression models forecast next quarter's sales figures.”

Data points indexed in time order

“Time series analysis detected seasonal patterns in demand.”

Identifying unusual patterns that don't conform to expected behavior

“Anomaly detection caught the security breach within minutes.”

Extract, Transform, Load - the data pipeline process

“The ETL pipeline processes millions of records nightly.”

A sequence of processes

“The data pipeline cleans and transforms the raw input.”

The representation of an object, situation, or set of information as a chart or other image

“Data visualization helps in identifying trends.”