Astermind Premium

Premium Machine Learning Toolkit - Advanced Extreme Learning Machine (ELM) variants and enterprise features built on top of Astermind Pro and Astermind Elm.

Overview

Astermind Premium extends Astermind Pro and Astermind Elm with 21 advanced ELM variants designed for enterprise use cases. Premium includes all features from Pro (RAG, Reranking, Summarization, Information Flow Analysis) plus specialized ELM architectures for:

• Online/Streaming Learning: Adaptive and Forgetting Online ELM
• Hierarchical Classification: Multi-level decision trees
• Attention Mechanisms: Attention-Enhanced ELM
• Uncertainty Quantification: Variational ELM
• Time-Series Analysis: Time-Series ELM
• Transfer Learning: Pre-trained model adaptation
• Graph Neural Networks: Graph ELM and Graph Kernel ELM
• Kernel Methods: 8 specialized kernel ELM variants
• Deep Architectures: Deep Kernel ELM
• Convolutional & Recurrent: CNN and RNN-style ELM
• Fuzzy Logic: Fuzzy ELM
• Quantum-Inspired: Quantum-Inspired ELM
• Tensor Operations: Tensor Kernel ELM

Installation

npm install @astermind/astermind-premium

Peer Dependencies

Astermind Premium requires:

• @astermind/astermind-pro (automatically installed as a dependency)
• @astermind/astermind-elm (included via Pro)

License Setup

Astermind Premium requires a valid license token to use premium features.

Getting Your License Key

To get started with Astermind Premium, visit our getting started page:

👉 Get Your License Key →

The getting started page provides step-by-step instructions for:

• Creating a free trial account
• Obtaining your license token
• Setting up your development environment

Setting Your License

Option 1: Environment Variable (Recommended)

export ASTERMIND_LICENSE_TOKEN="your-license-token-here"

Option 2: Programmatic Setup

import { setLicenseTokenFromString, initializeLicense } from '@astermind/astermind-premium';

// Initialize license system
initializeLicense();

// Set your license token
await setLicenseTokenFromString('your-license-token-here');

Option 3: Configuration File

// src/config/license-config.ts
export const LICENSE_TOKEN = 'your-license-token-here';

License Validation

Premium requires a valid license token. Invalid or expired tokens will be rejected.

Quick Start

import { 
  AdaptiveOnlineELM,
  HierarchicalELM,
  VariationalELM,
  initializeLicense,
  setLicenseTokenFromString
} from '@astermind/astermind-premium';

// Initialize license
await initializeLicense();
await setLicenseTokenFromString(process.env.ASTERMIND_LICENSE_TOKEN);

// Use Adaptive Online ELM for streaming data
const model = new AdaptiveOnlineELM({
  categories: ['positive', 'negative', 'neutral'],
  initialHiddenUnits: 64
});

// Train on batch data
const X = [[1, 2, 3], [4, 5, 6], [7, 8, 9]];
const y = [0, 1, 0];
model.fit(X, y);

// Predict
const predictions = model.predict([1, 2, 3], 3);
console.log(predictions);

Premium ELM Variants

1. Adaptive Online ELM

Dynamically adjusts hidden layer size based on performance.

import { AdaptiveOnlineELM } from '@astermind/astermind-premium';

const model = new AdaptiveOnlineELM({
  categories: ['class1', 'class2'],
  initialHiddenUnits: 64,
  minHiddenUnits: 32,
  maxHiddenUnits: 256
});

// Batch training
model.fit(X, y);

// Online updates
model.update(newSample, newLabel);

2. Forgetting Online ELM

Online learning with exponential forgetting of old data.

import { ForgettingOnlineELM } from '@astermind/astermind-premium';

const model = new ForgettingOnlineELM({
  categories: ['class1', 'class2'],
  forgettingFactor: 0.95 // Higher = forgets slower
});

model.fit(X, y);
model.update(newSample, newLabel);

3. Hierarchical ELM

Multi-level classification with hierarchical structure.

import { HierarchicalELM } from '@astermind/astermind-premium';

const model = new HierarchicalELM({
  hierarchy: {
    'root': ['animal', 'plant'],
    'animal': ['mammal', 'bird'],
    'mammal': ['dog', 'cat']
  },
  rootCategories: ['root']
});

model.train(X, y.map(label => getHierarchicalPath(label)));
const predictions = model.predict(sample, 3);
// Returns: [{ path: ['root', 'animal', 'mammal', 'dog'], prob: 0.95 }]

4. Attention-Enhanced ELM

Uses attention mechanisms to focus on important features.

import { AttentionEnhancedELM } from '@astermind/astermind-premium';

const model = new AttentionEnhancedELM({
  categories: ['class1', 'class2'],
  attentionUnits: 128
});

model.train(X, y);
const predictions = model.predict(sample, 3);

5. Variational ELM

Provides uncertainty estimates with predictions.

import { VariationalELM } from '@astermind/astermind-premium';

const model = new VariationalELM({
  categories: ['class1', 'class2']
});

model.train(X, y);
const predictions = model.predict(sample, 3, true); // Include uncertainty
// Returns: [{ label: 'class1', prob: 0.9, uncertainty: 0.05, confidence: 0.95 }]

6. Time-Series ELM

Specialized for sequential/time-series data.

import { TimeSeriesELM } from '@astermind/astermind-premium';

const model = new TimeSeriesELM({
  categories: ['trend_up', 'trend_down', 'stable'],
  sequenceLength: 10
});

// Sequences: number[][][] - array of sequences, each sequence is number[][]
const sequences = [
  [[1, 2], [2, 3], [3, 4]], // Sequence 1
  [[5, 6], [6, 7], [7, 8]]  // Sequence 2
];
const labels = [0, 1];

model.train(sequences, labels);
const prediction = model.predict(sequences[0], 3);

7. Transfer Learning ELM

Adapts pre-trained models to new tasks.

import { TransferLearningELM } from '@astermind/astermind-premium';

const model = new TransferLearningELM({
  categories: ['new_class1', 'new_class2'],
  transferRate: 0.3 // How much to adapt from source
});

model.train(X, y);

8. Graph ELM

Processes graph-structured data.

import { GraphELM } from '@astermind/astermind-premium';

const model = new GraphELM({
  categories: ['type1', 'type2']
});

const graphs = [
  {
    nodes: [
      { id: 'n1', features: [1, 2, 3] },
      { id: 'n2', features: [4, 5, 6] }
    ],
    edges: [
      { source: 'n1', target: 'n2' }
    ]
  }
];
const labels = [0];

model.train(graphs, labels);
const prediction = model.predict(graphs[0], 3);

9. Adaptive Kernel ELM

Automatically selects optimal kernel parameters.

import { AdaptiveKernelELM } from '@astermind/astermind-premium';

const model = new AdaptiveKernelELM({
  categories: ['class1', 'class2'],
  kernelType: 'rbf' // 'rbf', 'polynomial', 'sigmoid'
});

model.train(X, y);

10. Sparse Kernel ELM

Efficient kernel ELM using landmark points.

import { SparseKernelELM } from '@astermind/astermind-premium';

const model = new SparseKernelELM({
  categories: ['class1', 'class2'],
  numLandmarks: 50 // Number of landmark points
});

model.train(X, y);

11. Ensemble Kernel ELM

Combines multiple kernel ELMs for robust predictions.

import { EnsembleKernelELM } from '@astermind/astermind-premium';

const model = new EnsembleKernelELM({
  categories: ['class1', 'class2'],
  numModels: 5 // Number of ensemble members
});

model.train(X, y);
const predictions = model.predict(sample, 3);
// Returns: [{ label: 'class1', prob: 0.9, votes: 4 }] // votes = ensemble agreement

12. Deep Kernel ELM

Multi-layer kernel transformations.

import { DeepKernelELM } from '@astermind/astermind-premium';

const model = new DeepKernelELM({
  categories: ['class1', 'class2'],
  numLayers: 3
});

model.train(X, y);

13. Robust Kernel ELM

Handles outliers and noisy data.

import { RobustKernelELM } from '@astermind/astermind-premium';

const model = new RobustKernelELM({
  categories: ['class1', 'class2'],
  outlierThreshold: 0.1
});

model.train(X, y);
const predictions = model.predict(sample, 3);
// Returns: [{ label: 'class1', prob: 0.9, isOutlier: false }]

14. ELM-KELM Cascade

Cascades standard ELM with Kernel ELM.

import { ELMKELMCascade } from '@astermind/astermind-premium';

const model = new ELMKELMCascade({
  categories: ['class1', 'class2']
});

model.train(X, y);

15. String Kernel ELM

Processes string/text data using string kernels.

import { StringKernelELM } from '@astermind/astermind-premium';

const model = new StringKernelELM({
  categories: ['positive', 'negative']
});

const strings = ['hello world', 'good morning', 'bad day'];
const labels = [0, 0, 1];

model.train(strings, labels);
const prediction = model.predict(['hello'], 3);

16. Convolutional ELM

Image-like data processing with convolutional features.

import { ConvolutionalELM } from '@astermind/astermind-premium';

const model = new ConvolutionalELM({
  categories: ['cat', 'dog'],
  filterSize: 3,
  numFilters: 16
});

// Images: number[][][] - array of 2D images
const images = [
  [[1, 2, 3], [4, 5, 6], [7, 8, 9]], // Image 1
  [[9, 8, 7], [6, 5, 4], [3, 2, 1]]  // Image 2
];
const labels = [0, 1];

model.train(images, labels);
const prediction = model.predict(images[0], 3);

17. Recurrent ELM

Sequential data with hidden state memory.

import { RecurrentELM } from '@astermind/astermind-premium';

const model = new RecurrentELM({
  categories: ['class1', 'class2'],
  hiddenSize: 64
});

const sequences = [
  [[1, 2], [2, 3], [3, 4]], // Sequence 1
  [[5, 6], [6, 7], [7, 8]]  // Sequence 2
];
const labels = [0, 1];

model.train(sequences, labels);
const predictions = model.predict(sequences[0], 3);
// Returns: [{ label: 'class1', prob: 0.9, hiddenState: [...] }]

18. Fuzzy ELM

Fuzzy logic-based classification with membership functions.

import { FuzzyELM } from '@astermind/astermind-premium';

const model = new FuzzyELM({
  categories: ['low', 'medium', 'high']
});

model.train(X, y);
const predictions = model.predict(sample, 3);
// Returns: [{ label: 'medium', prob: 0.8, membership: 0.85, confidence: 0.9 }]

19. Quantum-Inspired ELM

Uses quantum computing principles for feature transformation.

import { QuantumInspiredELM } from '@astermind/astermind-premium';

const model = new QuantumInspiredELM({
  categories: ['class1', 'class2'],
  numQubits: 8
});

model.train(X, y);
const predictions = model.predict(sample, 3);
// Returns: [{ label: 'class1', prob: 0.9, quantumState: [...], amplitude: 0.95 }]

20. Graph Kernel ELM

Graph-structured data using graph kernels.

import { GraphKernelELM } from '@astermind/astermind-premium';

const model = new GraphKernelELM({
  categories: ['type1', 'type2']
});

const graphs = [
  {
    nodes: [{ id: 'n1', features: [1, 2] }],
    edges: [{ source: 'n1', target: 'n2' }]
  }
];
const labels = [0];

model.train(graphs, labels);

21. Tensor Kernel ELM

3D tensor data processing.

import { TensorKernelELM } from '@astermind/astermind-premium';

const model = new TensorKernelELM({
  categories: ['class1', 'class2']
});

// Tensors: number[][][] - array of 3D tensors
const tensors = [
  [
    [[1, 2], [3, 4]], // Channel 1
    [[5, 6], [7, 8]]  // Channel 2
  ]
];
const labels = [0];

model.train(tensors, labels);
const prediction = model.predict(tensors[0], 3);

API Reference

License Management

initializeLicense(): void

Initializes the license runtime. Called automatically on first use.

setLicenseTokenFromString(token: string): Promise<void>

Sets the license token from a string. Validates the token.

requireLicense(): void

Throws an error if no valid license is available. Called automatically by all Premium ELM variants.

checkLicense(): boolean

Returns true if a valid license is available, false otherwise.

getLicenseStatus(): LicenseState

Returns detailed license status information.

Common ELM Interface

All Premium ELM variants follow a similar interface:

interface ELMConfig {
  categories: string[];
  // ... variant-specific options
}

class PremiumELM {
  constructor(config: ELMConfig);
  train(X: any[], y: number[]): void;
  predict(sample: any, topK?: number): Prediction[];
}

Integration with Astermind Pro

Premium includes all features from Astermind Pro:

• RAG (Retrieval-Augmented Generation)
• Reranking
• Summarization
• Information Flow Analysis
• All Pro ELM variants

import { 
  RAGPipeline,
  Reranker,
  Summarizer,
  AdaptiveOnlineELM // Premium variant
} from '@astermind/astermind-premium';

Related Packages

• Astermind Pro - Advanced ML toolkit with RAG, reranking, and more
• Astermind Elm - Core Extreme Learning Machine library
• Astermind Synthetic Data - Synthetic data generation

License

Proprietary - Requires valid license token from license.astermind.ai

Support

• Documentation: docs.astermind.ai
• Issues: GitHub Issues
• Email: [email protected]
• Website: astermind.ai

Changelog

1.0.0

• Initial release
• 21 Premium ELM variants
• License validation
• Full integration with Astermind Pro
• Comprehensive test suite

Built with ❤️ by AsterMind AI