Feature frequency vs. presnces Figure 3(1)使用特征频率来生成文本向量。作者将“出现频率”改变成“是否出现”(如果出现,ni(d)=1,否则ni(d)=0),得到了 Figure 3(2),使预测结果提高了。于是,在接下来的实验中,作者采纳了上述的改变。 Bigrams 跳过 Parts of speech Figure 3(5) 通过Oliver Mason's Qt...
Rechenthin, M. D. (2014), "Machine-Learning Classification Techniques for The Analysis And Prediction Of High-Frequency Stock Direction" PhD thesis, University of Iowa, 1-260, https://ir.uiowa.edu/cgi/viewcontent.cgi?article=5248&context=etd...
Nowadays, many industries have been dealing with very large data sets of different types. Manually processing all that information can be time-consuming and might not even add value in the long term. Many strategies, from simple automation to machine learning techniques, are being applied for a ...
Machine learning classification with natural language processing (NLP) Working with more complex text classification tasks requires natural language processing or NLP. NLP lies at the intersection of several disciplines – linguistics, statistics, and computer science techniques that allow computers to unders...
This work examines the application of machine learning (ML) algorithms to evaluate dissolved gas analysis (DGA) data to quickly identify incipient faults in oil-immersed transformers (OITs). Transformers are pivotal equipment in the transmission and dist
Machine learning techniques based on artificial intelligence methods are debated in order to depict how machine learning algorithms can be used for image data classification. Several methods for objects identification and extraction are implemented in an image processing mobile software using an open ...
Classification of SD-OCT images using Deep learning approach Diabetic Macular Edema (DME)Deep learningFeature MatricesVisual Graphic Geometry (VGG)Glaucoma is the major reason that causes blindness today. It results in... M Awais,H Müller,F Meriaudeau - IEEE Icsipa 被引量: 9发表: 2017年 加...
This study examines the effectiveness of state-of-the-art supervised machine learning methods in conjunction with different feature types for the task of automatic annotation of fragments of clinical text based on codebooks with a large number of categories. We used a collection of motivational inter...
Machine learning techniques Abdulhamit Subasi, in Practical Machine Learning for Data Analysis Using Python, 2020 3.5.1 Classification Classification-based tasks are a subfield of supervised machine learning in which the key goal is to predict output labels or reactions that are categorical in nature...
Tasks include observation and attribute selection as well as transformation and cleaning of the data. Several ML techniques are then selected in the modeling phase and applied to the prepared dataset, before their parameters are calibrated to optimal values. The evaluation phase determines which ML ...