# evaluation
Using Django querysets effectively
https://blog.etianen.com/blog/2013/06/08/django-querysets/ https://docs.djangoproject.com/en/3.1/ref/models/querysets/#iterator queryset cache evalua
Evaluation Metrics in Machine Learning - ROC / AUC
Receiver Operation Curve (ROC) and Area Under Curve (AUC) are important evaluation metrics used in evaluating the performance of the binary classifica
Evaluation Metrics in Machine Learning - F1 Score
F1-score is the weighted average of precision and recall. Hence, since it takes both FP and FN into account, better the balance between precision and
Evaluation Metrics in Machine Learning - Precision / Recall
Precision and Recall are evaluation metrics which emphasize the performance in positive data-set. Precision = (TP) / (TP + FP) ratio of correctly pr
Evaluation Metrics in Machine Learning - Confusion Matrix
Confusion Matrix which is often used as an evaluation metrics in binary classification shows how much the model is confused while performing the predi
Evaluation Metrics in Machine Learning - Accuracy
So far, we have studied various techniques (ex- train/test-split, GridSearchCV, Standardization, Normalization, Data Preprocessing) to enhance our mac
(번역) 머신러닝 모델의 평가지표
과연 어떻게 머신러닝 모델의 완성도를 측정할까? 언제 학습(train)과 학습평가(evaluation)를 끝내고, 완성했다고 말할 수 있을까? 이 글을 통해, 이 질문에 대한 답을 찾아보자.