Ms. Dan Zhang Profile

Dan Zhang

at North China University of Technology

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 14 December 2021 Paper

Research on naive Bayes algorithm based on feature weighted

Dan Zhang, Yinglan Fang, Hui Tang

Proceedings Volume 12087, 120871A (2021) https://doi.org/10.1117/12.2624729

KEYWORDS: Feature extraction, Distance measurement, Mining, Machine learning, Information technology, Data modeling, Analytical research

Read Abstract +

The traditional naive bayes algorithm is a commonly used text classification algorithm, it’s attribute independence assumptions reduce the classification effect of text to some extent. In response to this problem, a weighted naive bayes text classification algorithm based on improved feature weight was proposed. First, when the TFIDF algorithm was improved from the inverse characteristic frequency, the category frequency, etc., the redundant attribute was removed, and the weight of the different feature items are used to measure the weight of different feature items, and then use the cross entropy. The feature item weight was substituted into a naive bayes formula, and the weighted naive bayes classification algorithm was constructed. Compared with several different algorithms, the experimental results show that this algorithm has significant increase in precision, recall and F1 score.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years