Class: FastText::Vectorizer
- Inherits:
-
Model
- Object
- Model
- FastText::Vectorizer
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- Defined in:
- lib/fasttext/vectorizer.rb
Constant Summary
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- DEFAULT_OPTIONS =
{
lr: 0.5,
lr_update_rate: 100,
dim: 100,
ws: 5,
epoch: 5,
min_count: 1,
min_count_label: 0,
neg: 5,
word_ngrams: 1,
loss: "ns",
model: "skipgram",
bucket: 2000000,
minn: 3,
maxn: 6,
thread: 3,
t: 0.0001,
verbose: 2,
pretrained_vectors: "",
save_output: false,
seed: 0,
autotune_validation_file: "",
autotune_metric: "f1",
autotune_predictions: 1,
autotune_duration: 60 * 5,
autotune_model_size: ""
}
Instance Method Summary
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Methods inherited from Model
#dimension, #initialize, #quantized?, #save_model, #sentence_vector, #subword_id, #subwords, #word_id, #word_vector, #words
Instance Method Details
#analogies(word_a, word_b, word_c, k: 10) ⇒ Object
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# File 'lib/fasttext/vectorizer.rb', line 41
def analogies(word_a, word_b, word_c, k: 10)
m.analogies(k, word_a, word_b, word_c).map(&:reverse).to_h
end
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#fit(x) ⇒ Object
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# File 'lib/fasttext/vectorizer.rb', line 31
def fit(x)
input = input_path(x)
@m ||= Ext::Model.new
m.train(DEFAULT_OPTIONS.merge(@options).merge(input: input))
end
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#nearest_neighbors(word, k: 10) ⇒ Object
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# File 'lib/fasttext/vectorizer.rb', line 37
def nearest_neighbors(word, k: 10)
m.nearest_neighbors(word, k).map(&:reverse).to_h
end
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