API Documentation

Introduction

Welcome to the NCS-API documentation! The Neural Clustering System API provides high-performance clustering algorithms through a simple REST interface. Our API supports multiple clustering algorithms including K-Means, DBSCAN, Hierarchical clustering, and our proprietary NCS Neural algorithm.

Key Features

• Process up to 1M data points in real-time
• Sub-100ms response times for most operations
• Multiple clustering algorithms with automatic parameter optimization
• Built-in data validation and preprocessing
• Comprehensive metrics and quality scoring
• WebSocket support for real-time streaming

Quick Start

Get up and running with the NCS-API in under 5 minutes. Here's a simple example to perform clustering on your data:

// Install: npm install @ncs-api/client
import { NCSClient } from '@ncs-api/client';

const client = new NCSClient({
  apiKey: 'your-api-key',
  baseURL: 'https://api.ncs-clustering.com/v1'
});

// Prepare your data
const data = [
  { x: 1.5, y: 2.3, feature3: 0.8 },
  { x: 2.1, y: 1.9, feature3: 1.2 },
  { x: 3.4, y: 4.1, feature3: 2.1 }
  // ... more data points
];

// Run clustering
async function runClustering() {
  try {
    const result = await client.cluster({
      algorithm: 'ncs',
      data: data,
      parameters: {
        neuralDepth: 3,
        learningRate: 0.05
      }
    });
    
    console.log('Clusters found:', result.clusters);
    console.log('Processing time:', result.processingTime);
    console.log('Quality metrics:', result.metrics);
  } catch (error) {
    console.error('Clustering failed:', error);
  }
}

runClustering();

# Install: pip install ncs-api-client
from ncs_api import NCSClient
import pandas as pd

# Initialize client
client = NCSClient(
    api_key='your-api-key',
    base_url='https://api.ncs-clustering.com/v1'
)

# Prepare your data
data = pd.DataFrame({
    'x': [1.5, 2.1, 3.4],
    'y': [2.3, 1.9, 4.1],
    'feature3': [0.8, 1.2, 2.1]
})

# Run clustering
try:
    result = client.cluster(
        algorithm='ncs',
        data=data.to_dict('records'),
        parameters={
            'neural_depth': 3,
            'learning_rate': 0.05
        }
    )
    
    print(f"Clusters found: {result['clusters']}")
    print(f"Processing time: {result['processing_time']}ms")
    print(f"Silhouette score: {result['metrics']['silhouette_score']}")
    
except Exception as error:
    print(f"Clustering failed: {error}")

curl -X POST https://api.ncs-clustering.com/v1/cluster \
  -H "Authorization: Bearer your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "algorithm": "ncs",
    "data": [
      {"x": 1.5, "y": 2.3, "feature3": 0.8},
      {"x": 2.1, "y": 1.9, "feature3": 1.2},
      {"x": 3.4, "y": 4.1, "feature3": 2.1}
    ],
    "parameters": {
      "neural_depth": 3,
      "learning_rate": 0.05
    }
  }'

Authentication

The NCS-API uses API keys for authentication. Include your API key in the Authorization header of all requests:

Authorization: Bearer your-api-key

Getting Your API Key

1. Sign up for a free account at dashboard.ncs-api.com
2. Navigate to the API Keys section
3. Generate a new API key with appropriate permissions
4. Copy and securely store your API key

Rate Limits

To ensure fair usage and optimal performance, the NCS-API implements rate limiting based on your subscription plan:

Rate limit headers are included in all responses:

X-RateLimit-Limit: 300
X-RateLimit-Remaining: 299
X-RateLimit-Reset: 1640995200

Clustering Endpoints

NCS Neural Algorithm

Our proprietary Neural Clustering System (NCS) uses deep learning techniques to identify complex patterns and clusters in high-dimensional data.

Parameters

JavaScript SDK

The official JavaScript/TypeScript SDK provides a convenient interface for integrating NCS-API into web and Node.js applications.

Installation

npm install @ncs-api/client

Basic Usage

import { NCSClient } from '@ncs-api/client';

const client = new NCSClient({
  apiKey: process.env.NCS_API_KEY,
  baseURL: 'https://api.ncs-clustering.com/v1',
  timeout: 30000
});

// Async/await syntax
try {
  const result = await client.cluster({
    algorithm: 'ncs',
    data: yourData,
    parameters: { neural_depth: 4 }
  });
  console.log(result);
} catch (error) {
  console.error('Error:', error.message);
}

// Promise syntax
client.cluster({
  algorithm: 'kmeans',
  data: yourData,
  parameters: { k: 3 }
})
.then(result => console.log(result))
.catch(error => console.error(error));

Real-time Streaming

// Subscribe to real-time clustering updates
const stream = client.createStream({
  algorithm: 'ncs',
  parameters: { neural_depth: 3 }
});

stream.on('data', (chunk) => {
  // Process incoming data point
  console.log('New data:', chunk);
});

stream.on('cluster_update', (clusters) => {
  // Handle cluster updates
  console.log('Updated clusters:', clusters);
});

stream.on('error', (error) => {
  console.error('Stream error:', error);
});

// Send data to stream
stream.write({ x: 1.5, y: 2.3, z: 0.8 });