rmf categorization

. Naive Bayesian classifier has two kinds of polynomial model and Bernoulli model when it is used in text classification, and the algorithm realizes these two models and is used for spam detection respectively, which has remarkable performance.Note: Personally, the "machine learning Combat" naive Bayesian chapter on the text classification algorithm is wrong, whether it is its Bernoulli model ("word set") or polynomial model (the book is called "word bag"), because its calculation formula does n

predict_proba should not be taken too seriously. Another limitation of Naive Bayes is the hypothesis of independent prediction. In real life, this is almost impossible, and there are more or less mutual effects between the variables. 4 Applications of Naive BayesReal-time predictions: no doubt, naive Bayes soon.multi-Class prediction: This algorithm is known for its multi-class predictive capabilities, so it can be used to predict the probability of multiple target variables.text

Text categorization problem: given document P (may contain title T), categorize documents into one or more of the N categoriesText classification applications: Common spam identification, sentiment analysisText classification direction: mainly two categories, multi-classification, multi-label classificationText Classification methods: Traditional machine learning Methods (Bayesian, SVM, etc.), deep learning methods (FASTTEXT,TEXTCNN, etc.)The processi

= Np.zeros ((3, 9)) Self.class_str = [] Self.m_card.set_card (2 *, 6) Self.mat_row = 3000 Self.i_file = 0 Self.class_tail = Np.array ([0.0] * self.mat_row) Self.word_count = Np.zeros (3000 9), float) # used to record the most common 3 million fragments self.class_score = Np.array ([0.0] * 9) Self.root_dir = "" Self.max _word_length = 5 Self.re_ch = re.compile (u "[\u4e00-\u9fa5]+", Re. u) Self.re_eng = re.compile (u "[a-za-z0-9+\[emailprotected]]+", Re. U) Self.fazhi = 3 def set_dict_cla

]-qout quantizing the classifier [0]-dsub Size of each sub-vector [2] What is the function that can be entered when the is execute (). -dim, vector length, default 100-D; -wordngrams, Word type, general can choose 2, two-tuple -verbose, the details of the output information, 0-2, different levels of detail (0 represents nothing). -LR: Learning rate [0.1] -lrupdaterate: Changing the rate of update rates [+] -dim: Word vector size [?] -ws: Context window size [5] -epoch: Number of loops [5] - NE

invention of entropy solved the problem completely. Worship Shannon. 』 specifically to text categorization, we now have a term ti that calculates its information gain to determine whether it is useful for categorization. So, first look at the entropy of the document without any features, that is, when there are no features to classify, how much information we have. After considering the feature, how much

For child window controls, sometimes we might want to get some messages from a subwindow, such as having three buttons under a main window, and if you want to use the Keyboard tab or the Shift-tab key to switch the focus between different buttons, you can use the Subwindow Class (window subclassing) method.Subcategory of child window:The window message handler for the button control is internal to Windows. However, by calling GetWindowLong with the Gwl_wndproc identifier as a parameter, you can

://github.com/richliao/textClassifier (Keras)Https://github.com/ematvey/hierarchical-attention-networks (TensorFlow)Https://github.com/EdGENetworks/attention-networks-for-classification (Pytorch)I'm a split line.[5] Recurrent convolutional neural Networks for Text classificationSiwei Lai et al.Chinese Academy of SciencesAAAI 2015https://www.aaai.org/ocs/index.php/AAAI/AAAI15/paper/viewFile/9745/9552This article presents a cyclic convolution neural network for text

. The number of glimpse in each experiment is fixed.2. Because the image in the dataset is constantly changing, the size of the "foveal" glimpses patches is consistent with the scale of the shortest edge of the input image.3. Replace LSTM with "vanilla" RNN, at Glimpse N, $r _n^{(1)}$ and $r _n^{(2)}$ are composed of 4,096 points, when $i = 1, 2$, $r _n (i) $ and $r _{n+1} (i) $ are fully connected.4. This article does not glimpse visual core $G _{image} (x_n| W_{image}) $ and $G _{loc} (l_n| W_

info:precision:0.764recall:0.759f1-score:0.760*************************Knn*************************Predict info:precision:0.642recall:0.635f1-score:0.636*************************Svm*************************Predict info:precision:0.777recall:0.774f1-score:0.7744. Clustering[CPP]View Plaincopy ###################################################### #KMeans Cluster From Sklearn.cluster import Kmeans Print ' *************************\nkmeans\n************************* ' pred

In work development , multiple projects are often created in Eclipse , but it is very inconvenient to Manage multiple projects. In particular , the equivalent of an Android project, you can not put a number of similar project files in a project to simplify the interface classification , this time in the Eclipse Create a working set in .Steps1, Click the lower triangle in the package Explorer view to toggle the view , the Top level Element option selects the working Set Working Set , You can sw

(CJ) =n (CJ)/n,p (d (TI) | CJ) = (n (ti, CJ) +1)/(n (CJ) +m), where N (CJ) represents the number of text in the training text that belongs to the Cj class, N is the amount of training text, N (ti, CJ) represents the number of training text containing feature TI in the category Cj, and M represents the total number of feature items inJust calculate all categories of P (cj| D), and then which is larger, which category the document belongs to. 3. Rocchio classifierThe basic idea of the Rocchio cla

In recent days to see a text categorization program, write the specific implementation process. Sometimes I see the algorithm, I feel very clear, but I do not know when to achieve. This time from a practical process, may be able to better understand. The first is the training dataset and the test data set. One line per document, mainly including Feature selection is divided into the following several steps: 1. Set the dimension of eigenvector: genera

For example, when publishing an article, the article is classified into related columns based on the value of a field. How should we implement it? For example, when publishing an article, the article is classified into related columns based on the

Upload. asp/wdread. asp method = post> topic: Author: Release date: Upload file: Sent to URL: /users/ size = 20> Wdread. asp /scripts/cpshost. dll? PUBLISH? Wdwriter. asp method = post name = form1>Upload file: /users/wdls> 'During the

This article is divided into two cases, introduced in recursion and do not use recursion in the case of Php Unlimited class classification, PHP infinite Classification in our development process is very long to see, our future development will be

An article that adds a level-1 category to a level-2 category is a query of all the following sub-categories. However, if you select a level-1 category when adding an article, the front-end will not display the articles it has added because all