Answers.Body: <p>If you want to classify data with similar characteristics, it would often helps if you hand craft features. For classifying women or men wrestling, you may want to try using cv2 to track human faces and feed that to your CNN as input. Example: <a href="https://realpython.com/face-recognition-with-python/" rel="nofollow noreferrer">https://realpython.com/face-recognition-with-python/</a></p>
  
  <p>If the data is not images, you may want to do a analysis to see which feature have no clear relationship with whether it is men or women wrestling and remove them. Example: <a href="https://towardsdatascience.com/a-feature-selection-tool-for-machine-learning-in-python-b64dd23710f0" rel="nofollow noreferrer">https://towardsdatascience.com/a-feature-selection-tool-for-machine-learning-in-python-b64dd23710f0</a></p>
  
  <p>Hope that I can help you and have a nice day! </p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2019-11-02T15:12:07.770Z
Answers.LastActivityDate: 2019-11-02T15:12:07.770Z
Answers.UserDisplayName: Clement
Body: <p>I have a dataset which has two very similar classes (men wrestling, women wrestling). I've used InceptionV3 as a classifier to solve the problem of classifying this dataset. Unfortunately, the accuracy of this classifier doesn't hit more than 70%. Is there any suggestion about how I can overcome this problem or any other similar problems?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2019-11-02T08:56:07.000Z
Comments.Text: How much data do you have?
Comments.UserDisplayName: GKozinski
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2019-11-02T09:54:10.393Z
Comments.Text: About ten thousand.
  Regardless of amount of data, I would be grateful for any suggestion
Comments.UserDisplayName: Arashsyh
Tags: <classification><tensorflow><keras>
Title: The best way of classifying a dataset including classes with high similarity?
UserDisplayName: Arashsyh
ThreadText: # The best way of classifying a dataset including classes with high similarity?
  
  (Asked by: username_0 on 2019-11-02)
  
  I have a dataset which has two very similar classes (men wrestling, women wrestling). I've used InceptionV3 as a classifier to solve the problem of classifying this dataset. Unfortunately, the accuracy of this classifier doesn't hit more than 70%. Is there any suggestion about how I can overcome this problem or any other similar problems?
  
  **Tags:** classification, tensorflow, keras
  
  > **Comments:**
  > **username_1**: How much data do you have?  
  > **username_0**: About ten thousand. Regardless of amount of data, I would be grateful for any suggestion  
  
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  ## 1 answers
  
  ### Answer by username_2 on 2019-11-02. Score: 1
  
  If you want to classify data with similar characteristics, it would often helps if you hand craft features. For classifying women or men wrestling, you may want to try using cv2 to track human faces and feed that to your CNN as input. Example: <https://realpython.com/face-recognition-with-python/>
  
  If the data is not images, you may want to do a analysis to see which feature have no clear relationship with whether it is men or women wrestling and remove them. Example: <https://towardsdatascience.com/a-feature-selection-tool-for-machine-learning-in-python-b64dd23710f0>
  
  Hope that I can help you and have a nice day!
  
  
  ---
  
  