Dataset

Upload CSV or Excel with a target column

Try with a sample dataset

Pick one to explore instantly — no upload needed

Neighbors & Distance

KNN

Core KNN configuration

N Neighbors (k)5

Sensitive (1)Smooth (50)

Weights

All k neighbors contribute equally to the vote.

Distance Metric

Minkowski Power (p)2

Manhattan (1)Euclidean (2)Higher

Algorithm

Auto picks the fastest structure based on data shape and metric.

Leaf Size30

Small (10)Large (100)

Train / Test Split

Holdout proportion for evaluation

Test Size20%

Train: 80%Test: 20%

Preprocessing

Feature transformations (scaling enforced for KNN)

Enable preprocessing

Advanced settings

Projection

2D visualization method

PCA for quick linear projection. UMAP for complex manifolds.

Parameter Guide

Click to expand

Performance Metrics

Accuracy

—

Awaiting training

Precision

—

Awaiting training

Recall

—

Awaiting training

F1 Score

—

Awaiting training

ROC AUC

—

Awaiting training

Dataset

—

Awaiting training

K-Optimizer

Suggest Optimal K

Cross-validation sweep to find the best number of neighbors

Classification Visualization

Classification Results

Interactive scatter plot of classification results

Run training to render the scatter plot

Advanced Analysis

Deep Dive Analysis

Run training or prediction to populate analysis

Run training or prediction to see results here.

Job History

Recent jobs — auto-pruned to keep 10 per type

No jobs recorded yet. Run a clustering, classification, or pipeline job to see results here.

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Dataset

Upload CSV or Excel with a target column

Try with a sample dataset

Pick one to explore instantly — no upload needed

Neighbors & Distance

KNN

Core KNN configuration

N Neighbors (k)5

Sensitive (1)Smooth (50)

Weights

All k neighbors contribute equally to the vote.

Distance Metric

Minkowski Power (p)2

Manhattan (1)Euclidean (2)Higher

Algorithm

Auto picks the fastest structure based on data shape and metric.

Leaf Size30

Small (10)Large (100)

Train / Test Split

Holdout proportion for evaluation

Test Size20%

Train: 80%Test: 20%

Preprocessing

Feature transformations (scaling enforced for KNN)

Enable preprocessing

Advanced settings

Projection

2D visualization method

PCA for quick linear projection. UMAP for complex manifolds.

Parameter Guide

Click to expand

Performance Metrics

Accuracy

—

Awaiting training

Precision

—

Awaiting training

Recall

—

Awaiting training

F1 Score

—

Awaiting training

ROC AUC

—

Awaiting training

Dataset

—

Awaiting training

K-Optimizer

Suggest Optimal K

Cross-validation sweep to find the best number of neighbors

Classification Visualization

Classification Results

Interactive scatter plot of classification results

Run training to render the scatter plot

Advanced Analysis

Deep Dive Analysis

Run training or prediction to populate analysis

Run training or prediction to see results here.

Job History

Recent jobs — auto-pruned to keep 10 per type

No jobs recorded yet. Run a clustering, classification, or pipeline job to see results here.

K-Nearest Neighbors (KNN) Classifier — Interactive Analysis