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Anonymous Customer

2018-01-17

The forms are very easy to fill out. I was unable to comments in a few places where I ran out of room for heirs and needed to include a comment to refer to an additional page.

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User in Consumer Electronics

2019-05-28

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User friendly, simple easy to use. Makes sending and receiving documents easy and professionals .
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Nothing really. Easy way to handle PDF's.
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Getting documents signed.

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How do you classify text?

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:

What are the classification of text?

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.

What is meant by text classification?

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.

Which model is best for text classification?

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.

How does text classification work?

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.

How do you classify a document?

Expectation maximization (EM) Naive Bayes classifier. Tfidf. Instantaneously trained neural networks. Latent semantic indexing. Support vector machines (SVM) Artificial neural network. K-nearest neighbor algorithms.

How can I improve my text classification?

Broke the documents in list of words. Removed stop words, punctuations. Performed stemming. Replaced numerical values with '#sum#' to reduce vocabulary size. Transformed the documents into TF-IDF vectors.

How do you text a classification?

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:

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