R: K-Nearest Neighbor(KNN) Regressor

hanaml.KNNRegressor {hana.ml.r}

R Documentation

K-Nearest Neighbor(KNN) Regressor

Description

hanaml.KNNRegressor is an R wrapper for PAL KNN algorithm for regression.

Usage

hanaml.KNNRegressor(conn.context,
                   data = NULL,
                   key = NULL,
                   features = NULL,
                   label = NULL,
                   n.neighbors = NULL,
                   aggregate.type = NULL,
                   metric = NULL,
                   minkowski.power = NULL,
                   algorithm = NULL,
                   categorical.variable = NULL)

Arguments

`conn.context`	`ConnectionContext` The connection to the SAP HANA system.
`data`	`DataFrame` DataFrame containing the data.
`key`	`character` Name of the ID column of data.
`features`	`list of character, optional` Names of the feature columns. If features is not provided, it defaults to all non-ID, no-label columns.
`label`	`character` Name of the column in data that specifies the dependent variable.
`n.neighbors`	`integer, optional` Number of nearest neighbors.#' Defaults to 1.
`aggregate.type`	`("uniform", "distance-weighted"), optional` Method used for averaging the values of the K-nearest neighbors. Defaults to 'distance-weighted'.
`metric`	`("manhattan", "euclidean", "minkowski", "chebyshev"), optional` Ways to compute the distance between data points. Defaults to 'euclidean'.
`minkowski.power`	`double, optional` When 'Minkowski' is used for metric, this parameter controls the value of power. Defaults to 3.0.
`algorithm`	`("brute-force", "kd-tree"), optional` Algorithm used to compute the nearest neighbors. Defaults to 'brute-force'.
`categorical.variable`	`character or list of characters, optional` Integer columns in the data table that should be treated as category variable.

Format

R6Class object.

Details

K-Nearest Neighbor (KNN) is a memory-based classification or regression method with no explicit training phase. For regression purpose, it assumes that instances should have similar values to their nearest neighbors.

Value

A "KNNRegressor" object.

Examples

## Not run: 
Training data:

> df.train$Collect()
   ID X1   X2 X3 VALUE
1   0  2    1  A     1
2   1  3   10  A    10
3   2  3   10  B    10
4   3  3   10  C     1
5   4  1 1000  C     1
6   5  1 1000  A    10
7   6  1 1000  B    99
8   7  1  999  A    99
9   8  1  999  B    10
10  9  1 1000  C    10

knr <- hanaml.KNNRegressor(conn.context = conn, data = df.train, key = "ID",
                           features = c("X1", "X2", "X3"),
                           label = "VALUE", n.neighbors = 3,
                           aggregate.type = "uniform",
                           algorithm = "brute-force",
                           categorical.variable = c("X1"))

## End(Not run)

[Package hana.ml.r version 1.0.8 Index]