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Administrator in International Trade and Development
2018-12-21
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I like the most is you can process all the documents in computer no need to print any paper, save time, save money and save our environment.
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I do not like it is the soft ware does not allow to edit Chinese fonts, I wish that Chinese can be edited too. That will be greatest function.
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Already recommended to my team.
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2019-01-28
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I am able to neatly complete forms and send them electronically. Much better than filling in by hand.
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Create a new text classifier: Go to the dashboard, then click Create a Model, and choose Classifier: Upload training data: Next, you'll need to upload the data that you want to use as examples for training your model. Define the tags for your model: Tag data to train the classifier:
Text classification or Text Categorization is the activity of labeling natural language texts with relevant categories from a predefined set. In laymen terms, text classification is a process of extracting generic tags from unstructured text. These generic tags come from a set of pre-defined categories.
Text classification or Text Categorization is the activity of labeling natural language texts with relevant categories from a predefined set. In laymen terms, text classification is a process of extracting generic tags from unstructured text. These generic tags come from a set of pre-defined categories.
It exclusively compares the input text with the training texts included in the model. In other words, when you train a model you associate each category to sample texts, so that when you enter a text to classify, the system will compare it with the examples and will determine which one is the nearest.
Linear Support Vector Machine is widely regarded as one of the best text classification algorithms. We achieve a higher accuracy score of 79% which is 5% improvement over Naive Bayes.
Classification-division text structure is an organizational structure in which writers sort items or ideas into categories according to commonalities. It allows the author to take an overall idea and split it into parts for the purpose of providing clarity and description.
The Simplest way to do text categorization is to use bag-of-words representation. Words/ n-grams of words in each document could be used as features. With this you can represent every document as vector in metric space. Subsequently, you can apply clustering to group documents that are similar in terms of content.
0:24 4:25 Suggested clip Prepare your data for ML | Text Classification Tutorial Pt. 1 (Coding YouTubeStart of suggested client of suggested clip Prepare your data for ML | Text Classification Tutorial Pt. 1 (Coding
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