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@astermind/astermind-premium
Advanced tools
Premium Machine Learning Toolkit - Advanced Extreme Learning Machine (ELM) variants and enterprise features built on top of Astermind Pro and Astermind Elm.
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:
npm install @astermind/astermind-premium
Astermind Premium requires:
@astermind/astermind-pro (automatically installed as a dependency)@astermind/astermind-elm (included via Pro)Astermind Premium requires a valid license token to use premium features.
To get started with Astermind Premium, visit our getting started page:
The getting started page provides step-by-step instructions for:
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';
Premium requires a valid license token. Invalid or expired tokens will be rejected.
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);
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);
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);
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 }]
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);
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 }]
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);
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);
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);
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);
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);
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
Multi-layer kernel transformations.
import { DeepKernelELM } from '@astermind/astermind-premium';
const model = new DeepKernelELM({
categories: ['class1', 'class2'],
numLayers: 3
});
model.train(X, y);
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 }]
Cascades standard ELM with Kernel ELM.
import { ELMKELMCascade } from '@astermind/astermind-premium';
const model = new ELMKELMCascade({
categories: ['class1', 'class2']
});
model.train(X, y);
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);
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);
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: [...] }]
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 }]
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 }]
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);
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);
initializeLicense(): voidInitializes the license runtime. Called automatically on first use.
setLicenseTokenFromString(token: string): Promise<void>Sets the license token from a string. Validates the token.
requireLicense(): voidThrows an error if no valid license is available. Called automatically by all Premium ELM variants.
checkLicense(): booleanReturns true if a valid license is available, false otherwise.
getLicenseStatus(): LicenseStateReturns detailed license status information.
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[];
}
Premium includes all features from Astermind Pro:
import {
RAGPipeline,
Reranker,
Summarizer,
AdaptiveOnlineELM // Premium variant
} from '@astermind/astermind-premium';
Proprietary - Requires valid license token from license.astermind.ai
Built with ❤️ by AsterMind AI
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