File size: 958 Bytes
bbd259b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 |
import numpy as np
print("feature_builder module loaded")
def build_features(similarity: dict, sentiment: list, sarcasm: float, context_probs: list) -> np.ndarray:
"""
Build final feature vector for stance classification
similarity: dict (5 scores)
sentiment: [neg, neutral, pos]
sarcasm: float
context_probs: [pol_crit, nat_crit, pol_praise, nat_praise] (4 scores)
"""
features = [
similarity["pro_india"],
similarity["anti_india"],
similarity["pro_government"],
similarity["anti_government"],
similarity["neutral"],
sentiment[0], # negative
sentiment[1], # neutral
sentiment[2], # positive
sarcasm,
context_probs[0], # Political Criticism
context_probs[1], # National Criticism
context_probs[2], # Political Praise
context_probs[3] # National Praise
]
return np.array(features, dtype=np.float32)
|