extern crate naivebayes;
use naivebayes::NaiveBayes;
fn to_vec(line: &str) -> Vec<String> {
let tokens = line.split(" ");
let mut v: Vec<String> = Vec::new();
for token in tokens {
v.push(token.to_string());
}
return v;
}
fn main() {
let mut nb = NaiveBayes::new();
nb.train(&to_vec("great product"), &"positive".to_string());
nb.train(
&to_vec("the protection level is poor"),
&"negative".to_string(),
);
nb.train(
&to_vec("this is a great band I love them"),
&"positive".to_string(),
);
nb.train(
&to_vec("never buy this product it is too bad"),
&"negative".to_string(),
);
nb.train(&to_vec("i love the shoes"), &"positive".to_string());
nb.train(
&to_vec("good product happy with the purchase"),
&"positive".to_string(),
);
let to_classify: Vec<String> = to_vec("I love it is great");
let classification = nb.classify(&to_classify);
print!("classification = {:?}", classification);
}