Spatially Explicit Hyperparameter Optimization for Neural Networks

【電子書籍なら、スマホ・パソコンの無料アプリで今すぐ読める！】

Neural networks as the commonly used machine learning algorithms, such as artificial neural networks (ANNs) and convolutional neural networks (CNNs), have been extensively used in the GIScience domain to explore the nonlinear and complex geographic phenomena. However, there are a few studies that investigate the parameter settings of neural networks in GIScience. Moreover, the model performance of neural networks often depends on the parameter setting for a given dataset. Meanwhile, adjusting the parameter configuration of neural networks will increase the overall running time. Therefore, an automated approach is necessary for addressing these limitations in current studies. This book proposes an automated spatially explicit hyperparameter optimization approach to identify optimal or near-optimal parameter settings for neural networks in the GIScience field. Also, the approach improves the computing performance at both model and computing levels. This book is writtenfor researchers of the GIScience field as well as social science subjects.画面が切り替わりますので、しばらくお待ち下さい。
※ご購入は、楽天kobo商品ページからお願いします。
※切り替わらない場合は、こちらをクリックして下さい。
※このページからは注文できません。

この商品の詳細を調べる

: 本・雑誌・コミック » 洋書 » COMPUTERS ＆ SCIENCE