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Why does my Keras model learn to recognize the background?

I'm trying to train this Keras implementation of Deeplabv3+ on Pascal VOC2012, using the pretrained model (which was also trained on that dataset). I got weird results with the accuracy quickly converging to 1.0: 5/5 [==============================]…
Matt
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shifting the last column in the dataframe to the first place

While this question had relative answers, I couldn't find an efficient and robust way of doing it. I have to shift the last column in my data frame to the first without disturbing any of the other columns. How should I do this ? Thanks in advance.
VishwaV
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what is difference between the DDQN and DQN?

I think I did not understand what is the difference between DQN and DDQN in implementation. I understand that we change the traget network during the running of DDQN but I do not understand how it is done in this code. We put the…
user10296606
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How to debug data analysis?

I've came across the following problem, that I recon is rather typical. I have some large data, say, a few million rows. I run some non-trivial analysis on it, e.g. an SQL query consisting of several sub-queries. I get some result, stating, for…
Little Bobby Tables
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Robustness of ML Model in question

While trying to emulate a ML model similar to the one described in this paper, I seemed to eventually get good clustering results on some sample data after a bit of tweaking. By "good" results, I mean that Each observation was put in a cluster with…
Alerra
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What is the difference between SGD classifier and the Logisitc regression?

To my understanding, the SGD classifier, and Logistic regression seems similar. An SGD classifier with loss = 'log' implements Logistic regression and loss = 'hinge' implements Linear SVM. I also understand that logistic regression uses gradient…
Akash Dubey
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Multiple labels in supervised learning algorithm

I have a corpus of text with a corresponding topics. For example "A rapper Tupac was shot in LA" and it was labelled as ["celebrity", "murder"]. So basically each vector of features can have many labels (not the same amount. The first feature vector…
Salvador Dali
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Should use sklearn or tensorflow for neural networks?

I have just started learning Neural Networks for deep learning from cs231. I am trying to implement Neural Network in Python. I am looking at using Tensorflow or scikit-learn. What are some pros and cons of these libraries for this application?
Muaaz Arif
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Chi-square as evaluation metrics for nonlinear machine learning regression models

I am using machine learning models to predict an ordinal variable (values: 1,2,3,4, and 5) using 7 different features. I posed this as a regression problem, so the final outputs of a model are continuous variables. So an evaluation box plot looks…
Alex
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Activation function vs Squashing function

This may seem like a very simple and obvious question, but I haven't actually been able to find a direct answer. Today, in a video explaining deep neural networks, I came across the term Squashing function. This is a term that I have never heard or…
Mate de Vita
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What is the difference between Perceptron and ADALINE?

What is the difference between Perceptron and ADALINE?
Developer
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How do I figure out if subsets can be plotted in a normal Euler diagram?

In some cases, it may be impossible to draw Euler diagrams with overlapping circles to represent all the overlapping subsets in the correct proportions. This type of data then requires using polygons or other figures to represent each set. When…
asheeshr
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What does the long curve-shape t-SNE mean?

I use 1-D CNN input 1*512 size time series data which randomly fragment segment, the output will classify input into 10 classes. After training the CNN, I apply t-SNE to the prediction which I fed in testing data. In general, the output shape of…
Chiao Wei Yeh
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Should I rescale tfidf features?

I have a dataset which contains both text and numeric features. I have encoded the text ones using the TfidfVectorizer from sklearn. I would now like to apply logistic regression to the resulting dataframe. My issue is that the numeric features…
ignoring_gravity
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XGboost - Choice made by model

i am using XGboost to predict a 2 classes target variable on insurance claims. I have a model ( training with cross validation, hyper parameters tuning etc...) i run on another dataset. My question is : is there a way to know why a given claim has…
Fabrice BOUCHAREL
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