Greife auf kostenlose Karteikarten, Zusammenfassungen, Übungsaufgaben und Altklausuren für deinen computational data analysis Kurs an der Technical University of Denmark zu.
609
Karteikarten
74
Studierende
0
Lernmaterialien
OLS (ordinary least squares)
what: Loss funciton
how: takes the sum of squares of prediction error.
EPE (expected prediction error)
Ridge regression L2 (shrinkage)
What: introduces some bias to the training data
How: to the equation that the linear regression calculates adds a penalty to the slope2 to the loss function. Lambda value determines its severity.
Why: to reduce the variance on the test data.
KNearest Neighbor (KNN) classification
What: ML model
How: counts the K amount of nearest neighbors next to the item to predict.
Why:
KNearest Neighbor (KNN) regression
What: ML model
How: calculate the number based on the average distance to the K neighbors
Why
Unsupervised learning
What: Category to put ML models into
How: Doesnt have a label to compare correctness of prediction.
Why: used for feature generation, outlier detection, finding hidden patterns
Bias-Variance tradeoff
What: Term to describe that the training data may not represent the real patterns present,
How: introducing bias may reduce overall variance.
Why
Validation set
what: a separated segment of the data. where the hyperparameter tuning takes place.
how: on the training set many models with different hyperparameters are trained, and based on the validation set, the best is chosen to perform on the test set.
why: To choose the best hyperparameters.
Cross validation
what: a method to separate data to be able to do hyperparameter tuning
how: data is separated into k chunks, then, 1 is a validation set, rest is train. for each model loop until each set was a validation set.
why: If there is not enough data, then one would do this to ensure proper generalization.
1 standard error rule
what: a best practice for cross validation
how: get the model that has the least error, then return the model which is the simplest and is one standard error worse.
why: ?
Greife kostenlos auf tausende geteilte Karteikarten, Zusammenfassungen, Altklausuren und mehr zu.
Jetzt loslegen
