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// Import necessary libraries | ||
use std::collections::HashMap; | ||
use std::hash::{Hash, Hasher}; | ||
use std::io::{Read, Write}; | ||
use std::ops::{Add, Mul, Sub}; | ||
use std::vec::Vec; | ||
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// Define the neural network AI model | ||
pub struct NeuralNetwork { | ||
// Neural network layers | ||
layers: Vec<NeuralLayer>, | ||
} | ||
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// Implement the neural network AI model | ||
impl NeuralNetwork { | ||
// Create a new neural network AI model | ||
pub fn new(layers: Vec<NeuralLayer>) -> Self { | ||
NeuralNetwork { layers } | ||
} | ||
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// Make a prediction using the neural network AI model | ||
pub fn predict(&self, input: Vec<f64>) -> Vec<f64> { | ||
// Forward pass through the neural network | ||
let mut output = input; | ||
for layer in &self.layers { | ||
output = layer.forward_pass(output); | ||
} | ||
output | ||
} | ||
} | ||
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// Define the decision tree AI model | ||
pub struct DecisionTree { | ||
// Decision tree nodes | ||
nodes: Vec<DecisionTreeNode>, | ||
} | ||
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// Implement the decision tree AI model | ||
impl DecisionTree { | ||
// Create a new decision tree AI model | ||
pub fn new(nodes: Vec<DecisionTreeNode>) -> Self { | ||
DecisionTree { nodes } | ||
} | ||
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// Make a prediction using the decision tree AI model | ||
pub fn predict(&self, input: Vec<f64>) -> Vec<f64> { | ||
// Traverse the decision tree | ||
let mut output = input; | ||
for node in &self.nodes { | ||
output = node.traverse(output); | ||
} | ||
output | ||
} | ||
} | ||
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// Export the AI models | ||
pub use NeuralNetwork; | ||
pub use DecisionTree; |