final double[] discretizedFeatures = new double[lp.features().size()]; for (int i = 0; i < lp.features().size(); ++i) { discretizedFeatures[i] = Math.floor(lp.features().apply(i) / 16); } return new LabeledPoint(lp.label(), Vectors.dense(discretizedFeatures)); } }); // C...
fe = FeatureExtractor(sent, ppindex,"succ") _features.append(fe.features())return_features 开发者ID:tuxedocat,项目名称:ss2012,代码行数:14,代码来源:prepchecker_baseline.py feature_extractor.FeatureExtractor.features方法License
For simplicity, we use a pre-trained SVM model on handcrafted features [6] for the experimentation of this tool. 3. Overview of impacts and usages The goal of FeatureExtractor tool is to improve the transparency and explainability of code intelligence models. The tool is mainly used to ...
遇到AttributeError: module 'radiomics.featureextractor' has no attribute 'RadiomicsFeaturesExtractor'这样的错误通常意味着你尝试从radiomics.featureextractor模块中访问一个不存在的属性或类。在 PyRadiomics 库中,这通常是因为使用了错误的模块路径或类名。 PyRadiomics 是一个用于从医学影像中提取定量特征的 Python 库...
Extracting features from URLs to build a data set for machine learning. The purpose is to find a machine learning model to predict phishing URLs, which are targeted to the Brazilian population. - lucasayres/url-feature-extractor
Fast and Easy to use video feature extractor This repo aims at providing an easy to use and efficient code for extracting video features using deep CNN (2D or 3D). It has been originally designed to extract video features for the large scale video dataset HowTo100M (https://www.di.ens....
This proposed extractor extracts only relevant shape features for processing to reduce processing time and improve the result’s quality. The image samples are taken for a skin disease named skin lesions for this work. The dataset of ISIC and PH2 is used in this work for analysis. This FIFE ...
Features selectionCurrently the recognition of plants from leaves has been a field of research very studied, the current algorithms can perfectly classify the leaves of different families. However, for the current algorithms it is difficult to classify leaves belonging to the same family but different...
在下文中一共展示了Extractor.extract_features方法的1个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。 示例1: __init__ ▲点赞 9▼ # 需要导入模块: from extractor import Extractor [as 别名]# 或者: from extractor.Extr...
ct-block由两个分支组成,字母C代表卷积分支,字母T代表变压器分支。卷积分支遵循PointNet++的设计来提取局部特征。Transformer分支采用偏移注意力设计,提取全局特征。如果ct块由两个互不干扰且独立的分支组成,则无法完成局部特征和全局特征学习的相互指导,无法有效融合。因此,我们在ct块中增加了两个特征传输元件。第一个特...