rmf categorization

a long time, the object_json.py is a custom JSON encoding function that permanently saves the classifier object, only the load classifier file is required for later use, unless the classifier needs to be updated.The SVM classifier in the package defines two objects, Svmtrain and Svmclassifer, which, based on the training data, produce a SVM classifier through the SMO algorithm; the latter is only a SVM classifier, including support vectors generated by svmtrain, support vector set and get funct

spent a day on lime papers:Http://arxiv.org/pdf/1602.04938v1.pdfcareful reading and code reading, experiments, generally understand the author's design ideas. background:When we build the model, we often think that our model is not stable enough, will there be sample bias effect, p>>n time will not cross-fit? We check the model stability, we do some cross-validation to see the variance of the evaluation indicators is not big. However, if the sample is initially biased due to sampling bias, which

In the/portal-master/portal-impl/src/portal.properties file, the following configuration is available:# Input A list of sections that would be included as part of the form when# updating a site. #sites. form.update.main=details,categorization,site-url,site-Templatesites.form.update.seo=Sitemap, robotssites.form.update.advanced=default-user-associations,staging,analytics,content-sharing,recycle- Binsites.form.update.miscellaneous=custom-fields,display

middle line, the expression of the middle line is g (x) = 0, that is, wx+b=0, we also call this function classification surface.In fact it is easy to see, the middle of the dividing line is not the only one, we rotate it a little bit, as long as the two types of data can not be divided into a wrong, still achieve the above-mentioned effect, a little translation, can also. At this point, it involves a problem, which function is better when there are multiple classification functions for the same

-dimensional spaces To dig up more useful information; B. Problems with unbalanced classes; C. Avoid complex parameter optimization problems; d. Adjust the accuracy of the classifier according to the different application needs; Mis-categorization is a problem, especially when the defective is considered to be free of defects. Contribution: A. Introduction of the Multiple kernel learning technique for the first

-global visual descriptor for scene categorization and object detection (PAMI 2011) Feature coding and pooling Vgg feature encoding toolkit-source code for various state-of-the-art feature encoding methods-including standardHard encoding, kernel codebook encoding, locality-Constrained Linear Encoding, and Fisher kernel encoding. Spatial pyramid matching-source code for feature pooling Based on Spatial pyramid matching (widely used for image class

Http://www.blogjava.net/zhenandaci/archive/2008/08/31/225966.htmlAs mentioned above, in addition to the classification algorithm, the feature extraction algorithm for the classification text processing has a great impact on the final effect, and feature extraction algorithm is divided into feature selection and feature extraction two categories, wherein the feature selection algorithm has mutual information, document frequency, information gain, root test and so on ten kinds, In this paper, we f

contains the word. #为了限制分类器需要处理的特征的数目, we started building a list of the first 2000 most frequent words in the corpus. #然后, define a feature extractor that simply checks whether the word is in a given document. #一个文档分类的特征提取器, whose characteristics indicate whether each word all_words = NLTK in a given document. Freqdist (W.lower () for W in Movie_reviews.words ()) Word_features = List (all_words) [: Watts] def document_features ( Document): Document_words = Set (document) features = {} for Wo

previous example, but only the second and third elements in the array are categorized. Int[] keys = new INT[4]; Keys[0] = 11; KEYS[1] = 3; KEYS[2] = 8; KEYS[3] = 5; string[] names = new String[4]; Names[0] = "Howard, Ryan"; NAMES[1] = "Allen, Ray"; NAMES[2] = "Pujols, Albert"; NAMES[3] = "Iverson, Allen"; Array.Sort (keys, names, 1, 2); 　　Here is the corresponding vb.net code: Dim keys (3) as Integer Keys (0) = 11 Keys (1) = 3 Keys (2) = 8 Keys (3) = 5 Dim names (3) as String Names (0) = "Howar

For a content page article, if the content of the article is too long or there is a category (ranking), then the page reading is undoubtedly the best choice. If the content of an article does not involve categorization, such as a novel class, then the page number is displayed in the normal way, because the content is coherent and unlikely to exist. The possibility of skipping the middle content directly to read the following: But what if an articl

. Classification model 1) training, testing. 2 Common methods: Naive Bayesian, maximum entropy, SVM. 6. Evaluation indicators 1) Accuracy rate Accuracy = (TP + TN)/(TP + FN + FP + TN) reflects the ability of the classifier to judge the whole sample--------------------positive judgment, negative judgment negative. 2) Accuracy rate Precision = tp/(TP+FP) reflects the proportion of the true positive sample in the positive case determined by the classifier 3) Recall rate Recall = tp/(TP+FN) reflec

. Under the guarantee of certain probability, it overcomes the problem of high-dimensional feature query, but the author uses lsh combined with SIFT feature to practice the image retrieval experiment, because each image involves hundreds of features, then when querying a picture, it is necessary to carry on the characteristics of the query, even if the feature points of the query picture are filtered to 50% of the amount, The number of feature queries required for a picture query is also not a s

recognition and optimization for social image applications. The rekognition API enables emotional recognition and gender detection using the features of the eyes, mouth, nose, and face, and can be used to determine gender, age, and mood. Link: http://www.programmableweb.com/api/rekognition 12.Skybiometry face Detection and recognition: Provides facial detection and recognition services. The new version of the API contains features that distinguish sunglasses from transparent glasses. Link: htt

dialogue with Gan, was seq2seq+attention.1 2 3 4 5 6 7 Next question: Which NLP problem do you think may be suitable to be solved with Gan, the existing Gan method may pit too much, not necessarily suitable for that kind of NLP problem A: I think, gan to do half supervision or more hopeful, I think text categorization is a viable application B: Dialog Generation If there is an evaluation indicator should be able to do, but now there is no C: Ha, in m

, and is an important branch of artificial intelligence and intelligent science. It is also an early and active research field of artificial intelligence. Natural language processing includes two aspects of natural language understanding and natural language generation. Natural language Understanding Systems transform natural language into a form that computer programs are easier to handle and understand. The natural language generation system converts computer data related to natural language i