/** * Appends a bias (constant 1.0) to the end of each Vector in the dataset, * the original dataset is unmodified. The resulting Vectors will have one * greater dimension and look like: [ x1 x2 ] -> [ x1 x2 1.0 ] * @param dataset * Dataset to append a bias term to, Vectors can be of different * dimensionality * @return * Dataset with 1.0 appended to each Vector in the dataset */ public static ArrayList<Vector> appendBias( Collection<? extends Vector> dataset) { return DatasetUtil.appendBias(dataset, 1.0); }
/** * Appends a bias (constant 1.0) to the end of each Vector in the dataset, * the original dataset is unmodified. The resulting Vectors will have one * greater dimension and look like: [ x1 x2 ] -> [ x1 x2 1.0 ] * @param dataset * Dataset to append a bias term to, Vectors can be of different * dimensionality * @return * Dataset with 1.0 appended to each Vector in the dataset */ public static ArrayList<Vector> appendBias( Collection<? extends Vector> dataset) { return DatasetUtil.appendBias(dataset, 1.0); }
/** * Appends a bias (constant 1.0) to the end of each Vector in the dataset, * the original dataset is unmodified. The resulting Vectors will have one * greater dimension and look like: [ x1 x2 ] -> [ x1 x2 1.0 ] * @param dataset * Dataset to append a bias term to, Vectors can be of different * dimensionality * @return * Dataset with 1.0 appended to each Vector in the dataset */ public static ArrayList<Vector> appendBias( Collection<? extends Vector> dataset) { return DatasetUtil.appendBias(dataset, 1.0); }