이전
Learning 함수에서 학습한 ANN 모델로 새로운 메시지 감정분류(긍/부정, 희/노/애/락 등)에 대한 예측치와 예측력을 구하는 함수
LearningWeight,tags_1gram.csv
clean_test_message.csv
prediction_results.csv
- Reference file: (1) 아래 표처럼 Learning 함수에서와 동일한 tag 목록, 그리고 (2) Learning 함수의 output을 콤마(,)를 구분자로 하여 받아옴
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
- Input file: document 컬럼에 새로 감정 분류 라벨링을 하고자 하는 정제 텍스트가 있는 CSV 파일 @@컬럼명 다 contents로 통일하기로 했다?
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
- Output file: 새로운 input 메시지에 대한 모델 예측치와 예측력
- Output 예시
data:image/png;base64,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
긍정(1), 부정(0) 분류 예시.
Predicted_value(예측치)는 모델이 각 메시지에 대한 예측치를 산출한 것으로, 1에 가까울 수록 긍정, 0에 가까울수록 부정이다.
Prediction_accuracy(예측력)는 해당 예측이 정확할 확률은 얼마나 되는지를 나타낸 것이다. 가령, 첫번째 메시지는 0.943의
예측치가 나와 긍정 메시지로 예상되고, 이 예측이 정답일 확률은 0.959이다.
MessageClassifier_with_2gram_for_Prediction