Questions tagged [binary-classification]

For questions about binary classification problems, i.e. problems where we want to classify inputs into 1 of 2 classes.

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28 views

Is a test accuracy of 0.74 good enough, given a dataset of about 700 samples, and, if not, how can I improve it?

I am new to neural networks. I am trying to solve a binary classification problem. Specifically, I want to determine whether a patient has or not a certain disease based on the dataset. The dataset ...
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8 views

Can I perform 3D point cloud per-point labeling from binary classification alone?

All, It seems that the process of individually labeling points in 3D point clouds is no small task. I believe that's why tools like these exist: Sagemaker Pointly But ... what if there are only two ...
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25 views

Is it normal that we get different AUC results after running with various seeds?

We are working on optimizing a CNN made for binary image classification (by that I mean to classify each image to group A or group B). It is based on InceptionV3, using PyTorch. We saw that choosing ...
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18 views

How can I weight each point in one-class SVM?

I want to give weights to some data points Specifically, these are points related to anomalies (I'm implementing one-class SVM for anomaly detection) Exactly, I want to consider some data points that ...
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12 views

Evaluation metric for time-series anomaly detection

My dataset is time-series sensor data and anomaly ratio is between 5% and 6% 1. For time-series anomaly detection evaluation, which one is better, precision/recall/F1 or ROC-AUC ? When empirically ...
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1answer
120 views

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{...
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1answer
95 views

What are pros and cons of using a multi-head neural network versus a single neural network for multi-label classification?

I haven't been able to find a good discussion specifically comparing the two (only one describing a classification and regression problem). I am training a classifier to learn both age and gender ...
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19 views

Is my dataset unlearnable, or is my LSTM model not smart enough?

I have time-series data obtained from a video. The data is composed of bitrate and corresponding label pairs for each timestamp: The distribution over the first 30 seconds is as follows: I have ...
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34 views

Why am I not getting a good accuracy but bad precision and recall for this binary classification problem (with an unbalanced dataset)?

I'm working on a simple MLP classification problem where I need to have the output layer as softmax. The dataset that I've been using needs to pass through a parse that I made to remove NaN and change ...
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49 views

How to train a machine learning model with multiple attributes and one target value?

I'm working on a machine learning problem where I need to guess which customers will churn and which of them will continue to be customers. I have $X_0, X_1, X_2, X_3, X_4, X_5$ and $X_6$ attributes ...
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3answers
44 views

Is binary classification using CNN possible if the training data only consists of one class?

Is binary classification using CNN possible if the training data only consists of one class? I am working on landslide risk assessment using Convolutional Neural Networks and I want to train a network ...
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20 views

How to Classify Game Stages Based on Bitrate Time Series Data Using RNN - LSTM

I need suggestions for my project and would be glad if you would give me a hand. I have a dataset of frames obtained from the old-school game DOOM. Each frame in the dataset has the following columns: ...
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1answer
101 views

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 ...
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23 views

Can RNNs be used to classify these time series into two classes?

My task is to classify into two classes the time series like these shown in the figure. The figure shows one class on the left sub-figure and second one on the right. The series are shown in pairs ...
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2answers
77 views

Could I just choose the other (non-predicted) class when the accuracy is low?

I have a binary classification problem. My neural network is getting between 10% and 45% accuracy on the validation set and 80% on the training set. Now, if I have a 10% accuracy and I just take the ...
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1answer
365 views

Is it appropriate to use a softmax activation with a categorical crossentropy loss?

I have a binary classification problem where I have 2 classes. A sample is either class 1 or class 2 - For simplicity, lets say they are exclusive from one another so it is definitely one or the other....
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22 views

Should an increased learning rate for an adaptive linear neuron (ADALINE) reduce the square error at every epoch?

I am completely new to neural networks and therefore, my query may have some basic conceptual problem. I am following Fundamentals of Neural Networks by Laurene Fusett. In this book, the author ...
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1answer
64 views

Which approach should I use to classify points above and below a sine function $y(x) = A + B \sin(Cx)$?

In a linear regression problem, a line can divide a data set into two categories. So, basically, points above the line belong to category 1, and points below the ...
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1answer
32 views

Why are CNN binary classifier output probability distributions often skewed?

I've been working on a lot of simple resnet18 binary classifiers lately and I've started to notice that the probability distributions are often skewed one way or the other. This figure shows one such ...
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1answer
782 views

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 ...
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19 views

How to perform data augmentation on multiple input classification task?

I would like to add some more samples to my dataset which consists of two parts: 1. image and 2. numerical data. For each image in the dataset there is its corresponding numerical data as well. If it ...
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1answer
38 views

Semantic segmentation failing in small instance detection

I performed semantic segmentation with U-net. My dataset consists of grayscale images of defects. After training the dataset for I got an metric accuracy of only 0.3 - 0.4 IOU. Eventhough it is merely ...
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334 views

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 ...
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1answer
96 views

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 ...
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18 views

Is it a fair evaluation if each model of k-fold cross validation is trained with different epochs and the mean AUC score gathered out of k folds?

Let's say I have a dataset for binary classification. And I am going to conduct 5-fold cross-validation and get AUC scores for each fold (mean AUC score too). However, if I set the training epoch to $...
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1answer
37 views

Should binary feature be in one or two columns in deep neural networks?

Let's assume I have a simple feedforward neural network whose input contains binary 0/1 features and output is also binary two classes. Is it better, worse, or maybe totally indifferent, for every ...
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1answer
35 views

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 ...
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157 views

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 ...
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1answer
31 views

Image Classification for watermarks with poor results

Just starting learning things about tensorflow and NN. As an exercise I decided to create a dataset of images, watermarked and not, in order to binary classify these. First of all, the dataset ( you ...
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1answer
257 views

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 ...
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2answers
92 views

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 ...
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1answer
66 views

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 ...
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1answer
72 views

Are there any advantages of using rules-based approaches versus models for detecting spam?

Suppose that we have unlabeled data. That is, all we have are a collection of emails and want to determine whether any of them is spam or not. Let's say we have $1,000$ rules to determine whether a ...
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1answer
55 views

How many parameter would there be in a logistic regression model used to classify reviews into "good" or "bad"?

Suppose we want to classify a review as good ($1$) or bad ($0$). We have a training data set of $10,000$ reviews. Also, suppose we have a vocabulary of $100,000$ words $w_1, \dots, w_{100,000}$. So ...
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1answer
98 views

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 ...
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1answer
121 views

Why is my fine-tuned YOLO model detecting other objects as a human?

I am new to deep learning and computer vision. I have a problem where I use the YOLO to detect objects. For my problem, I just want to recognize 1 human only. So, I changed the final YOLO's layer (...
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4answers
171 views

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 ...