For unsupervised methods, we reported ARI only since matched cell labels are not directly available. Additionally, we benchmarked NeuCA with other neural network based methods (neural-network, scDeepSort32), and presented the results in Supplementary Fig. S16. Overall comparisons We provided an ...
methods to predict missing binding sites. Here we present GraphProt2, a computational RBP binding site prediction framework based on graph convolutional neural networks (GCNs). In contrast to current CNN methods, GraphProt2 offers native support for the encoding of base pair information as well as...
缺点:无法处理复杂的用户行为和数据输入。 neural network-based models 为了解决简单网络的表示学习不足问题,研究人员又给出了neural collaborative filtering(NCF)、deep factorization machine(DeepFM),实际上就是将神经网络和前面提到的CF、FM结合了起来。 缺点:仍然没有考虑到数据的高阶结构信息。(要注意到用户的偏好...
types. (d) Receiver operating characteristic (ROC) area under the curve (AUC) values based on five-fold cross-validation using different algorithms: neural network, random forest, support vector machines (SVM), k-nearest neighbor (KNN), quadratic discriminate analysis (QDA), and naïve Bayes. ...
《Neural Network Methods in Natural Language Processing》这本书给了答案,这本书是一本非常适合入门自然语言处理的书籍,足够薄,最关键的是有中文版。。。是哈工大车万翔老师团队翻译的,在一定程度上做到了权威。不过有的地方翻译的意思有出入,对照英文版就可以了。
搜索策略主要包括以下方法:random search(RS)、Bayesian optimization、evolutionary methods、reinforcement learning(RL)、gradient-based methods。 进化算法在几十年前就已经用来进化神经网络了,(Evolving artificial neural network)对2000年以前的进化算法做了literature review,可以参考查阅。
On the basis of the principle of neural network and the characteristics of project cost estimation,this paper establishes neural-network-based model of rapid estimation of project cost.The basic principle of this model is discussed.This paper also illustrates the method of establishing the model and...
Metric-based (or non-parametric) methods(基于度量(或非参数))。 这类方法关注了用于学习的特征,以及特征间的相似度。 “我们知道深度学习的成功来源于能够学习数据的特征表示,进一步说, 一个特征表示是, 不同的数据样例进来, 它们的特征向量的几何距离, 与其在语义空间的相似度相对应。这类似于学习了一个metric...
This study aimed to compare several clustering methods, particularly a deep neural network-based model, and identify the best clustering method with a maximally distinct 1-year outcome in patients with ischemic stroke. Prospective stroke registry data from a comprehensive stroke center from January ...
Fig. 3A summarizes the results of ADHD diagnosis for all the compared methods. The ROC curves of each method are depicted in Fig. 3B. The overall results show that deep neural network-based models surpass the traditional machine learning methods. Importantly, our proposed dGCN yields the best ...