Binary classification task performance.

<p>Each row is associated with a mental state and each outer column with a forecast horizon. For each of the 30 conditions, bar plots show XGBoost and LSTM test predictions. The bar height corresponds to the number of examples with each bar indicating the true class and colors reflecting the p...

وصف كامل

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Thierry Jean (20691795) (author)
مؤلفون آخرون:	Rose Guay Hottin (20691798) (author), Pierre Orban (62056) (author)
منشور في:	2025
الموضوعات:	Neuroscience Science Policy Mental Health Biological Sciences not elsewhere classified Information Systems not elsewhere classified thus providing richer results also showed previous research focused prediction targets derived passive sensor data mean absolute error machine learning algorithm g ., calm forecasting mental states extreme gradient boosting digital phenotyping studies clinical rating scales forecast mental states forecast horizon expanded 3 forecast horizons systematically overestimated performance often ordinal nature next week ). evaluating predictive performance 2 predictive tasks 2 learning algorithms xgboost models performed using performance metrics forecast tasks ordinal regression xlink "> term memory small decrease similar levels significant yet seeing things remains unclear popular choices next day lstm models long short continuous regression binary classification best suited 73 %, 551 days
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

كن أول من يترك تعليقا!

Binary classification task performance.

مواد مشابهة