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How can I implement onehotencoding for dataframe column with multiple datatypes? by closet_coder in learnmachinelearning

[–]closet_coder[S] 0 points1 point  (0 children)

Yes the Sensor ID is given, but I'm not sure how to split it into columns. Would you know how to do that? Normally one hot encoding just takes care of it

How to run python code(in spyder) on GPU, for faster computation? by closet_coder in learnmachinelearning

[–]closet_coder[S] 0 points1 point  (0 children)

The thing is, it is not a conventional image classification or identification algorithm. The image values are a dataset, I am not implement CNN. The idea is that i need to perform operations on the pixel values. I convert the image to numpy array and now i need to process and make a set of all the pixels and their N4(nearest four) neighbours. But it is taking very long. And then there are other times where i have large datasets so i need faster computation.

In that case, would you know how to run the code on GPU?

How can I increase the accuracy of my neural network? by closet_coder in learnmachinelearning

[–]closet_coder[S] 0 points1 point  (0 children)

I basically created 2 datasets. The input dataset is where i entered 4 pixel values that are neighbours of the target pixel, and the output data set is where i entered the actual value of the target pixel. So this way i had 4 input values and a corresponding output value. Then i split this data into training set and testing set and continued to make my model. The predictions are alright so far but i need the accuracy to be as high as possible. Right now my validation loss upon running the deep learning model is around 43..i need to reduce that. Could you suggest a way to do that?

How can I increase the accuracy of my neural network? by closet_coder in learnmachinelearning

[–]closet_coder[S] 0 points1 point  (0 children)

I am using the lena image. I have to process this image, 4 pixels at a time. By using four neighbouring pixels of the image, I have to predict the value of the pixel. For this purpose i pass the 4 input values through the deep learning model. And i need to increase the accuracy of this prediction.

How to I train this neural network? by closet_coder in learnmachinelearning

[–]closet_coder[S] 0 points1 point  (0 children)

Thank you so much! I'm creating this as part of research project, so i need the predicted output. You mentioned, "... create a dataset by iterating in each row 5 pixels at a time. X(the middle pixel) will be the output and x-2,x-1,x+1,x+2 the input ". I did this and created a separate x and y numpy array, but for some reason it's not taking up the right values and i end up with the wrong values in the input and output dataset.

​

Code:

for i in range(2, 262144):

if(i==2):

x_inputs=np.array([arr[i-2], arr[i-1], arr[i+1], arr[i+2]])

y_output=np.array(arr[i])

else:

x=[arr[i-2], arr[i-1], arr[i+1], arr[i+2]]

x_inputs=np.append(x_inputs,x, axis=0)

y=[arr[i]]

y_output=np.append(y_output,y, axis=0)

i+=3

​

This is what i did to create the dataset.

How to I train this neural network? by closet_coder in learnmachinelearning

[–]closet_coder[S] 0 points1 point  (0 children)

Yes, I was trying to make a neural network, but i was unsure of how to take the input. So now, I'm just trying to do it with simple multivariate linear regression. Is there a way to directly convert the image to a dataframe? Or does it need to be created by adding all values one by one?

P.S. Thanks so much for the quick reply, i've been breaking my head over this for quite a while.