KNN Alogorithm

Question

Is there anyone have any idea with this function in Python?

def test_knn(train_x, train_y, test_x, num_nn):
return None

def main():

# Read the data file
szDatasetPath = './letter-recognition.data' # Put this file in the same place as this script
listClasses = []
listAttrs = []
with open(szDatasetPath) as csvFile:
csvReader = csv.reader(csvFile, delimiter=',')
for row in csvReader:
listClasses.append(row[0])
listAttrs.append(list(map(float, row[1:])))

# Generate the mapping from class name to integer IDs
mapCls2Int = dict([(y, x) for x, y in enumerate(sorted(set(listClasses)))])

# Store the dataset with numpy array
dataX = np.array(listAttrs)
dataY = np.array([mapCls2Int[cls] for cls in listClasses])

# Split the dataset as the training set and test set
nNumTrainingExamples = 15000
trainX = dataX[:nNumTrainingExamples, :]
trainY = dataY[:nNumTrainingExamples]
testX = dataX[nNumTrainingExamples:, :]
testY = dataY[nNumTrainingExamples:]

Answer 1

Definition:- K Nearest Neighbour(KNN) is a simple algorithm that stores all the available cases and classifies the new data or case based on a similarity measure. It is mostly used to classifies a data point based on how its neighbours are classified.
Now coming to your question, the function above simply does data preprocessing. It reads data from csv file and converted it to some numpy arrays and split based on number of records needed, which then may be passed to knn algorithm. It may not be possible to say exactly what it does without looking into data.