I need guidance with the KNN algorithm

[Mobo01]

Hello everyone,

I’m trying to apply the K-Nearest Neighbours (KNN) method on a dataset in Python, but I’m getting an error that I can’t figure out. Could you please assist me in locating the problem?

Here’s the pertinent section of my code:

import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import MinMaxScaler
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import accuracy_score

# Custom dataset
X = np.array([[2, 4], [3, 6], [5, 8], [7, 10], [9, 12]])
y = np.array([0, 1, 0, 1, 0])

# Split the data into training and test sets
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

# Min-max scaling the features
scaler = MinMaxScaler()
X_train = scaler.fit_transform(X_train)
X_test = scaler.transform(X_test)

# Implement KNN
k = 3
knn = KNeighborsClassifier(n_neighbors=k)
knn.fit(X_train, y_train)

# Make predictions on the test set
y_pred = knn.predict(X_test)

# Calculate accuracy
accuracy = accuracy_score(y_test, y_pred)
print(f"Accuracy: {accuracy}")

I’m getting the following problem when I execute the code:

ValueError: Expected 2D array, got 1D array instead:
array=[0.14285714 0.57142857 1.        ]. Reshape your data either using array.reshape(-1, 1) 
if your data has a single feature or array.reshape(1, -1) if it contains a single sample.

I’m not sure what’s generating this issue, so I read this post to have a better understanding, but I couldn’t go past the “reshape” option. Could someone kindly help me figure out how to fix this mistake and get my code to operate properly? Thank you in advance for your assistance!

[WindLother]

This is a tough one…

The error message says:

@Mobo01

ValueError: Expected 2D array, got 1D array instead:

But in the code section you provided, there is no place where such an error should occur. Your X_train and X_test are already 2D arrays after the MinMaxScaler operation.

Can you give your full code? I think the error might be in another section.

[Idkwhttph]

try:

import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import MinMaxScaler
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import accuracy_score

# Custom dataset with overlapping data points
X = np.array(
    [[2, 4], [3, 6], [4, 8], [6, 9], [7, 10], [9, 12], [8, 11], [5, 7], [6, 5], [4, 6]]
)
y = np.array([0, 1, 1, 1, 1, 0, 0, 1, 1, 1])

# Split the data into training and test sets
X_train, X_test, y_train, y_test = train_test_split(
    X, y, test_size=0.2, random_state=42
)

# Min-max scaling the features
scaler = MinMaxScaler()
X_train = scaler.fit_transform(X_train)
X_test = scaler.transform(X_test)

# Implement KNN
k = 3
knn = KNeighborsClassifier(n_neighbors=k)
knn.fit(X_train, y_train)

# Make predictions on the test set
y_pred = knn.predict(X_test)

# Calculate accuracy
accuracy = accuracy_score(y_test, y_pred)
print(f"Accuracy: {accuracy}")

Does this work? I mean… it shows a accuracy of 1… which is obviously a fail. Atleast its not 0 lol. If this doesn’t solve the problem, then I can conclude that I am trash at python. Oh yes it means it works because @QwertyQwerty88 liked it. Hope this help ty.