About This Release > Statistical Python Functions > KNN_CLASSIFY: K-Nearest Neighbors Classification

KNN_CLASSIFY: K-Nearest Neighbors Classification

K-nearest neighbors classification is a method for assigning a class membership to a data point in the space spanned by the predictors. The classification is done by assigning the class most common among its k nearest neighbors. This method requires having a distance definition in this space.

Reference: Calculate a K-Nearest Neighbors Classification 

KNN_CLASSIFY(options, neighbors, power,
        predictor_field1[, predictor_field2, ...] target_field)

where:

options

Reserved for future use.

neighbors

Integer

Is the number of nearest neighbors to participate in the prediction.

power

Integer

Is the power (p) of the L^p-distance.

  • power=1 calculates the distance as the sum of the absolute values of the differences between the coordinates (Manhattan distance).
  • power=2 calculates the distance as the square root of the sum of the squares of the differences between the coordinates (Euclidean distance).
predictor_field1[, predictor_field2, ...]

Numeric

Are one or more predictor field names.

target_field

Numeric

Is the target field.

Example: Predicting Education Level Using KNN_CLASSIFY

The following request uses KNN_CLASSIFY to predict education level using the 20 nearest neighbors and Euclidean distance, with predictors age, income, population range, and gender. The DEFINE FILE command creates virtual fields with correct numeric formats for use in the function. The data set includes rows with missing target values. 

DEFINE FILE WF_RETAIL
POP_CODE/I2 =
  DECODE WF_RETAIL_GEOGRAPHY_CUSTOMER.CITY_POPULATION_RANGE (
    'H: 100,001 - 250,000'       1,
    'I: 250,001 - 1,000,000'     2,
    'J: 1,000,001 - 10,000,000'  3,
    'K: 10,000,001 - 50,000,000' 4,
    ELSE 0  );
GENDER_CODE/I2 =
  DECODE WF_RETAIL_CUSTOMER.GENDER (
    'M' 1, 'F' 0 );
END

TABLE FILE WF_RETAIL
PRINT ID_CUSTOMER AGE INCOME  DEGREE_M  EDUC_LEVEL_M
COMPUTE ED_PRED/I2=KNN_CLASSIFY(' ',20,2,
                                AGE,
                                INCOME,
                                POP_CODE,
                                GENDER_CODE,
                                EDUC_LEVEL_M);
WHERE POP_CODE NE 0;
WHERE OUTPUTLIMIT IS 8;
ON TABLE SET PAGE NOLEAD
ON TABLE SET STYLE *
GRID=OFF,$
ENDSTYLE
END

Partial output is shown in the following image.

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