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Showing posts with the label Machine Learning
Performing 1d Convolution Using 2d Kernel In Keras

Performing 1d Convolution Using 2d Kernel In Keras

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I am currently working on a CNN network, in which i want to apply a 2d kernel on a image, but it on… Read more Performing 1d Convolution Using 2d Kernel In Keras
Groupby With Sub-ranges In Pandas

Groupby With Sub-ranges In Pandas

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I am researching soccer dataset LEAGUE HOME DRAW AWAY WINNER PREDICTED PROFIT 0 … Read more Groupby With Sub-ranges In Pandas
Ntlk & Python, Plotting Roc Curve

Ntlk & Python, Plotting Roc Curve

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I am using nltk with Python and I would like to plot the ROC curve of my classifier (Naive Bayes). … Read more Ntlk & Python, Plotting Roc Curve
Shape Mismatch: If Categories Is An Array, It Has To Be Of Shape (n_features,)

Shape Mismatch: If Categories Is An Array, It Has To Be Of Shape (n_features,)

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Here is the code I'm trying to execute to encode the values of the first column of my data set … Read more Shape Mismatch: If Categories Is An Array, It Has To Be Of Shape (n_features,)
Why Roc_auc Produces Weird Results In Sklearn?

Why Roc_auc Produces Weird Results In Sklearn?

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I have a binary classification problem where I use the following code to get my weighted avarege pr… Read more Why Roc_auc Produces Weird Results In Sklearn?
Using Sgd Without Using Sklearn (logloss Increasing With Every Epoch)

Using Sgd Without Using Sklearn (logloss Increasing With Every Epoch)

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def train(X_train,y_train,X_test,y_test,epochs,alpha,eta0): w,b = initialize_weights(X_train[0]… Read more Using Sgd Without Using Sklearn (logloss Increasing With Every Epoch)