Questions tagged [binary-classification]
For questions about binary classification problems, i.e. problems where we want to classify inputs into 1 of 2 classes.
60 questions
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Threshold Classifier
I have a simple classifier that classifies incoming values based on a threshold value. The threshold value is 0.005. The classification is as follows: thresh == 0.005: if value <= thresh: class == ...
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1answer
63views
Treating binary classification as 3 class problem with two cutoffs -- what metric to use?
So I have a binary classification problem, however I don't want to predict on places where the model isn't very confident. So let's say for a probability output between 0.4 & 0.7, I return no ...
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How to design a neural network where input consist of binary bits and output has discrete amplitudes?
The array size of input and output are different (e.g.: 88 - 176). Order of data points are matter it should not change. Also i want to make sure the reversibility like when i give amplitudes(...
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1answer
35views
How to incorporate the probability threshold for binary classification into scikit-learn GridSearchCV? [closed]
How would I perform grid search in scikit-learn including over the probability threshold for binary classification? In my search, most answers suggest first fitting a model and then performing a loop ...
2votes
1answer
85views
If the output is 0.09, does this mean that the prediction is class 1 or 0?
I use a Keras EfficientNetB7 and transfer learning to solve a binary classification problem. I use tf.keras.layers.Dense(1, activation="sigmoid")(x) for ...
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1answer
383views
Does the root node of a Decision Tree change when one data point is removed?
I recently took an online quiz on Machine Learning. One question was particularly confusing to me. The question is stated below. Consider a dataset Z on which a decision tree is built. Consider the ...
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1answer
307views
Image segmentation with varying resolution
I am looking to create a model that is able to perform binary segmentation of images with varying resolutions. For model should be able to classify tree or not tree regardless of the resolution of the ...
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1answer
65views
Computer vision algorithms for binary classification of bird images
I want to start a project to detect if an image is a crow or not a crow (crow as in the black bird). Is this referred to as "binary classification?" If I wanted to use open source Python ...
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What are the most common fault prediction algorithms?
I have to predict a fault (automotive related) as much in advance as possible. Right now I have found a solution that is somewhat satisfactory (a good number of true positives and a low number of ...
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Why does a neural network struggle to solve this simple problem?
Consider the following problem: Given a vector x of size dim with values between 0 and 1 (exclusive), determine if ...
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-1votes
1answer
192views
I’m making a simple neural network from scratch and it won’t learn anything. Please help [closed]
I am coding a classifier neural network from scratch. It is not really learning and I believe that somewhere there is a gradient explosion/vanishing issue. Could be some other stuff as well that I ...
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1answer
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Why does KNN Model return 99% accuracy on dataset with default parameters? [closed]
I am building a model that predicts if a user will like a stock or not based on different features, such as Market Cap, Current Ratio, Sector, Trailing PE, etc. I am going to implement this model in a ...
0votes
1answer
77views
How to evaluate binary classifier on imbalanced dataset?
I have trained a Decision Tree model on an imbalanced dataset. I got the following results for the test set from the sklearn and imblearn classification reports (attached below). Moreover, the other ...
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570views
How to specify categorical features in cat boost?
I have a dataset (pandas data frame) with all features of type int32 containing continuous values except one feature state_number, its data type is int32, but it ...
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0votes
1answer
167views
How to interpret binary classification metrics on an imbalanced data set?
I have an imbalanced dataset on intrusion detection. I have (attack class) 3668045 samples and (benign class) 477 samples. I made a 70:30 Train test split. My problem is to predict whether the given ...
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