For questions about binary classification problems, i.e. problems where we want to classify inputs into 1 of 2 classes.
Questions tagged [binary-classification]
58 questions
7
votes
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How should we interpret this figure that relates the perceptron criterion and the hinge loss?
I am currently studying the textbook Neural Networks and Deep Learning by Charu C. Aggarwal. Chapter 1.2.1.2 Relationship with Support Vector Machines says the following:
The perceptron criterion is a shifted version of the hinge-loss used in…
The Pointer
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4
votes
3 answers
In logistic regression, why is the binary cross-entropy loss function convex?
I am studying logistic regression for binary classification.
The loss function used is cross-entropy. For a given input $x$, if our model outputs $\hat{y}$ instead of $y$, the loss is given by
$$\text{L}_{\text{CE}}(y,\hat{y}) = -[y \log \hat{y} +…
hanugm
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4
votes
2 answers
Does summing up word vectors destroy their meaning?
For example, I have a paragraph that I want to classify in a binary manner. But because the inputs have to have a fixed length, I need to ensure that every paragraph is represented by a uniform quantity.
One thing I've done is taken every word in…
Arnav Das
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3
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3 answers
If we want to classify something as either a cat/dog or neither, do we need 2 or 3 classes?
Suppose one trains a CNN to determine if something was either a cat/dog or neither (2 classes), would it be a good idea to assign all cats and dogs to one class and everything else to another? Or would it be better to have a class for cats, a class…
John M.
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3
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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 max(0.05 / x) > 1.
Obviously, this is a trivial problem to solve with conventional means.
However, what strikes me as interesting is…
Daniel
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3
votes
1 answer
Is there a way to update the neural network to fit the new data without the time required for retraining?
I built a basic neural network in MATLAB. The neural network classifies points on the X-Y axis system into two classes (0 and 1).
(I try to get the function that represents a shape from this photo)
Every so often the values of the points change…
shlomo odem
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3
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How to use residual learning applied to fully connected networks?
Is there any reason why skip connections would not provide the same benefits to fully connected layers as it does for convolutional?
I've read the ResNet paper and it says that the applications should extend to "non-vision" problems, so I decided to…
rocksNwaves
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2
votes
1 answer
How can I use Generative Adversarial Networks to solve the imbalanced class problem?
Problem setting
We have to do a binary classification of data given a training dataset $D$, where most items belong to class $A$ and some items belong to class $B$, so the classes are heavily imbalanced.
Approach
We wanted to use a GAN to produce…
frederik
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2
votes
1 answer
How to get more accuracy of the logistic regression model?
I am working on a Baby Crying Detection model using logistic regression.
Out of $581$ audios, $222$ are of a baby crying. Each audio is of $5$ seconds.
what I have done is convert each audio into numbers. and those numbers go into a .csv file. so…
Muhammad Waqar Anwar
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2
votes
1 answer
What is the definition of the hinge loss function?
I came across the hinge loss function for training a neural network model, but I did not know the analytical form for the same.
I can write the mean squared error loss function (which is more often used for regression) as
$$\sum\limits_{i=1}^{N}(y_i…
hanugm
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2
votes
1 answer
Why doesn't the set $\{ -2, +2 \}$ in $E(X) = (y − \text{sign}\{\overline{W} \cdot \overline{X} \}) \in \{ −2, +2 \}$ include $0$?
I am currently studying the textbook Neural Networks and Deep Learning by Charu C. Aggarwal. Chapter 1.2.1.2 Relationship with Support Vector Machines says the following:
The perceptron criterion is a shifted version of the hinge-loss used in…
The Pointer
- 527
- 3
- 17
2
votes
1 answer
Support Vector Machine Convert optimisation problem from argmax to argmin
I'm new to the AI Stackexchange and wasn't certain if this should go here or to Maths instead but thought the context with ML may be useful to understand my problem. I hope posting this question here could help another student learning about Support…
Joneron
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2
votes
1 answer
Why am I getting a difference between training accuracy and accuracy calculated with Keras' predict_classes on a subset of the training data?
I'm trying to solve a binary classification problem with AlexNet. I split the original dataset into training and validation datasets using a 70/30 ratio. I have trained my neural network with a dataset of 11200 images, and I obtained a training…
Saha
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2
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2 answers
How to perform binary classification when one class is more predominant than the other?
Assuming we have big $m \times n$ input dataset, with $m \times 1$ output vector. It's a classification problem with only two possible values: either $1$ or $0$.
Now, the problem is that almost all elements of the output vector are $0$s with a very…
Marvin
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2
votes
1 answer
Which loss function should I use for binary classification?
I plan to create a neural network using Python, Keras, and TensorFlow. All the tutorials I have seen so far are concerned with image recognition. However, the goal of my program would be to take in 10+ inputs and calculate a binary output…
IUBIU
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