Using Image Data along with CSV file data for CNN model
$begingroup$
I have image data along with csv file where each row of csv file contains attributes for corresponding image.
I want to use images as well as csv file data to build CNN model using Keras.
What is preferred way of doing it?
- I can append the attribute data with numpy array of image and train the model.
- I can create 2 different models and use average/voting for prediction.
I think, in 1st appraoch csv file data which has around 50 columns would hardly matter as image shape is (128*128*3). Is it correct? and how can I give more importance to csv file (like 60% weightage to image data and 40% to csv file).
And again how CNN would work with that CSV file data as CNN is preferred on Image Data?
machine-learning python deep-learning keras cnn
$endgroup$
add a comment |
$begingroup$
I have image data along with csv file where each row of csv file contains attributes for corresponding image.
I want to use images as well as csv file data to build CNN model using Keras.
What is preferred way of doing it?
- I can append the attribute data with numpy array of image and train the model.
- I can create 2 different models and use average/voting for prediction.
I think, in 1st appraoch csv file data which has around 50 columns would hardly matter as image shape is (128*128*3). Is it correct? and how can I give more importance to csv file (like 60% weightage to image data and 40% to csv file).
And again how CNN would work with that CSV file data as CNN is preferred on Image Data?
machine-learning python deep-learning keras cnn
$endgroup$
add a comment |
$begingroup$
I have image data along with csv file where each row of csv file contains attributes for corresponding image.
I want to use images as well as csv file data to build CNN model using Keras.
What is preferred way of doing it?
- I can append the attribute data with numpy array of image and train the model.
- I can create 2 different models and use average/voting for prediction.
I think, in 1st appraoch csv file data which has around 50 columns would hardly matter as image shape is (128*128*3). Is it correct? and how can I give more importance to csv file (like 60% weightage to image data and 40% to csv file).
And again how CNN would work with that CSV file data as CNN is preferred on Image Data?
machine-learning python deep-learning keras cnn
$endgroup$
I have image data along with csv file where each row of csv file contains attributes for corresponding image.
I want to use images as well as csv file data to build CNN model using Keras.
What is preferred way of doing it?
- I can append the attribute data with numpy array of image and train the model.
- I can create 2 different models and use average/voting for prediction.
I think, in 1st appraoch csv file data which has around 50 columns would hardly matter as image shape is (128*128*3). Is it correct? and how can I give more importance to csv file (like 60% weightage to image data and 40% to csv file).
And again how CNN would work with that CSV file data as CNN is preferred on Image Data?
machine-learning python deep-learning keras cnn
machine-learning python deep-learning keras cnn
asked 10 mins ago
SociopathSociopath
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236210
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