Questions tagged [classification]

For questions related to the placement of individual cases into categories, such as is essential in fraud detection, spam detection, quality control, prediction of user or market responses, automated organizing or indexing, assigning objects in view to types of obstacles or risks, writing or typing recognition, phonic recognition, .

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What kind of optimizer is suggested to use for binary classification of similar images?

I have spent some time searching Google and wasn't able to find out what kind of optimization algorithm is best for binary classification when images are similar to one another. I'd like to read ...
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21 views

Difference between training accuracy and calculating accuracy with class prediction

I have trained my neural network with a dataset of 11200 images, and its validation accuracy was 96%. I saved my model and load its weights to the same neural network. I chose 738 images of my dataset ...
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61 views

Why is there more than one way of calculating the accuracy?

Some sources consider the true negatives (TN) when computing the accuracy, while some don't. Source 1: https://medium.com/greyatom/performance-metrics-for-classification-problems-in-machine-learning-...
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31 views

Why does the machine learning algorithm need to learn a set of functions in the case of missing data?

I am currently studying the textbook Deep Learning by Goodfellow, Bengio, and Courville. Chapter 5.1 Learning Algorithms says the following: Classification with missing inputs: Classification ...
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28 views

When is it time to switch to deep neural networks from simple networks in text classification problems?

I did an out of domain detection task (as a binary classification problem) and tried LR and Naive Bayes and BERT but the deep neural network didn't perform better than LR and NB. For the LR I just ...
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1answer
27 views

Can I provide a CNN with hints?

Let's say I want to classify a dataset of handwritten digits (CNNs on their own can get 99.7% on the MNIST dataset but let's pretend they can only get 90% for the sake of this question). Now, I ...
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1answer
27 views

How should I penalize the model proportionally to the error?

I am making an MNIST classifier. I am using categorical cross-entropy as my loss function. I want to make it so that if the correct label is 3, then it will penalize the model less heavily if it ...
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14 views

Tensorflow neural network - inherent overfitting in certain X and Y distributions?

Really open ended question here... I'm working on a classifier model that is used to predict whether some amount is > x, ...
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1answer
49 views

Is there a mathematical theory behind why MLP can classify handwritten digits?

I'm trying to really understand how multi-layer perceptrons work. I want to prove mathematically that MLP's can classify handwritten digits. The only thing I really have is that each perceptron can ...
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1answer
25 views

I need to select the image from a predefined dataset that are the closest to the input, is this possible or do I even need to use ML/AI?

So as the title states, I have a set of images and I want to process input images and need to select the image that "looks" the most like the input image. I know I've seen something similar where the ...
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1answer
24 views

Hand-Signs Recognition using Deep Learning Convolutional Neural Networks

I am developing a CNN model to recognize 24 hand-signs of American Sign Language. I have 2500 Images/hand-sign. The data split is: Training = 1250 Images/hand-sign Validation = 625 Images/hand-sign ...
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1answer
19 views

Does bag-of-words method improve the classification accuracy?

I'm a beginner in computer vision. I want to know which structure among the following two can get better accuracy of image classification. Structure 1: SIFT feature + SVM Structure 2: bag-of-word ...
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Post-classification after inference

I designed a fire detection using Deep Learning based classification approach. In my training dataset, I have both fire and fire smokes are supposed to be detected (all under "fire"; mostly real fires ...
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58 views

Why are the terms classification and prediction used as synonyms in the context of deep learning?

Why are the terms classification and prediction used as synonyms especially when it comes to deep learning? For example, a CNN predicts the handwritten digit. To me, a prediction is telling the next ...
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Can we train the model to detect real users with only positive labels?

We have hundreds of thousands of customers records, and we need to take the benefits of our data to train a model that will recognize fake entries or unrealistic ones for our platform, where customers ...
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1answer
44 views

What make a CNN suitable for image classification or for semantic segmentation?

I've just started with CNN and there is something that I haven't understood yet: How do you "ask" a network: "classify me these images" or "do semantic segmentation"? I think it must be something on ...
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51 views

Neural nets not learning mnist dataset

I tried training a 2 hidden layer network using the mnist dataset, but I am not getting any results. I have tried tuning the learning rate(tried 0.1 and 0.0001) and the number of epochs(tried 10 and ...
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1answer
36 views

What class of problem is this?

If I have a lot of input output pairs as training data <float Xi, float Yi> and I have a parametrized approximation function (I know the function algorithm, ...
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18 views

Stereoscopic vision, object rotation/distance

I am looking for some advice about deep learning. (sorry for my horrible English) I am thinking about making system which can detect objects and their rotation angles & positions in space. For ...
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70 views

Suggestion for finding the stable regions in spiral galaxy data?

I am working with a data set that consists of the actual pitch angle (given as PA(Y)) and the pitch angle at each radii (listed from 1 to 217). In the image below, ...
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3answers
54 views

How to correctly label images for multi-label classification?

I have images that contain lots of elements. Some I know, some I don't. I want to know if it's ok to only label those I do know. Let's take this image for example. I would label the green stuff and ...
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28 views

What's the mathematical relationship between number of trainable parameters and size of training set?

Let's say that I have a pre-trained model where the training set used to pretrain the model is very different from my training set. Let's say I unfreeze layers that have X trainable parameters. What ...
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1answer
39 views

Can training a model on a dataset composed by real images and drawings hurt the training process of a real-world application model?

I'm training a multi-label classifier that's supposed to be tested on underwater images. I'm wondering if feeding the model drawings of a certain class plus real images can affect the results badly. ...
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2answers
49 views

Is there any classifier that works best in general for NLP based projects?

I've written a program to analyse a given piece of text from a website and make conclusary classifications as to its validity. The code basically vectorizes the description (taken from the HTML of a ...
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Is it acceptable to use various training sets for the individual models when using a majority vote classifier?

So I am trying to use a majority vote classifier combining different models and I was wondering if it is acceptable to use different training sets for the individual models (including different ...
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1answer
58 views

Interpretation of feature selection based on the model

The description of feature selection based on a random forest uses trees without pruning. Do I need to use tree pruning? The thing is, if I don't cut the trees, the forest will retrain. Below in the ...
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19 views

Variable binning for NN

I come from a background of scorecard development using logistic regression. Steps involved there are: 1. binning of continuous variables into intervals (eg age can be binned into 10-15 years, 15-20 ...
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1answer
49 views

How difficult is this sound classification?

I want a microphone to pick up sounds around me (let's say beyond a 3 foot radius), but ignore sounds made at my desk, such as the rustling of paper, clicking a mouse and typing, my hands brushing up ...
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33 views

How to understand my CNN's training results?

I created a multi-label classification CNN to classify chest X-ray images into zero or more possible lung diseases. I've been doing some configuration tests on it and analyzing its results and I'm ...
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0answers
16 views

Can an image recognition model used for human pose estimation?

I am currently writing my thesis about human pose estimation and wanted to use Google's inception network, modify it for my needs and use transfer learning to detect human key joints. I wanted to ask ...
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1answer
42 views

How to classify human actions?

I'm quite new to machine learning (I followed the Coursera course of Andrew Ng and now starting deeplearning.ai courses). I want to classify human actions real-time like: Left-arm bended Arm above ...
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20 views

Human identification using gait analysis

I am working on a human identification by gait analysis project. So far, I have managed to extract the Gait Energy Image(GEI) of a silhouette. I am stuck on finding a way to move forward with my ...
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25 views

Outliers detection problem in neural networks

Assuming we have big m x n input dataset with m x 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 ...
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1answer
38 views

How to draw bounding boxes for gender classification?

I wonder what is the better way of drawing rectangles on images for gender classification. My task is to create a classifier (CNN based) to detect gender from pictures of entire bodies (not just faces)...
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2answers
123 views

How to use BERT as a Multi-Purpose Conversational AI?

After doing some more research, I thought I'd reframe my question a little. I’m looking to make an NLP model that can achieve a dual purpose. One purpose being that it can hold interesting ...
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1answer
46 views

Can a deep neural network be trained to classify an integer N1 as being divisible by another integer N2?

So I’ve been working on my own little dynamic architecture for a deep neural network (any number of hidden layers with any number of nodes in every layer) and got it solving the XOR problem ...
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28 views

Relationship between model complexity (depth) and dataset size

I'm new to deep learning. I was wondering what's the relationship between a deep model complexity (e.g. total number of parameters, or depth) and the dataset size? Assuming I want to do a binary ...
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12 views

Is there an algorithm for “contextual recognition” with probabilities?

Example 1 An object is composed of 3 sub-objects. Object 1: 90% looks like an eye 10% looks like a wheel Object 2: 50% looks like an eye 50% looks like a wheel Object 3: 90% looks like a mouth 10% ...
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64 views

How can I classify instances into two categories and then into sub-categories, when the number of features is high?

I'm working with a problem where I have a lot of variables for different cases of different users. Depending on the values of the different variables of a concrete user in a concrete case, the ...
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1answer
41 views

structure of neural network for classification problems with large amounts of null classifications

I am building a Convolution neural network to predict certain categories based on images (the location of a pointer on a surface) . However in many cases there will be no pointer in the view or ...
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1answer
38 views

How are the inputs passed to the neural network during training for the XOR classification task?

Let's suppose we have to train a neural network for the XOR classification task. Are the inputs $(00, 01, 10, 11)$ inserted in a sequential way? For example, we first insert the 00 and change the ...
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1answer
144 views

How can I minimise the false positives?

I have 50,000 samples. Of these 23,000 belong to the desired class $A$. I can sacrifice the number of instances that are classified as belonging to the desired class $A$. It will be enough for me to ...
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19 views

The membership function of Consequents (Outputs) in Fuzzy classifier

The problem in Iris data is to classify three species of iris (setosa, versicolor and virginica) by four-dimensional attribute vectors consisting of sepal length (x1) sepal width (x2) petal length (...
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1answer
29 views

Can I perform multiclass classification when the number of features is less than the number of targets?

Is it possible to perform multiclass classification on data where the number of features is less than the number of target variables? Do you have any suggestions on how to address a problem where I ...
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24 views

How to change the architecture of my simple sequential model

I'm new to Deep Learning with Keras. With some tutorials online for cat vs non-cat classification, I was able to compile this simple architecture for my own ...
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14 views

Model training with colored images instead of grayscale

I'm new to Python and Deep Learning with Keras. With some tutorials online for cat vs non-cat classification, I was able to compile this simple training code for my ...
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1answer
37 views

Feature extraction timeseries, model compatibility

I've got a timeseries with sensor data (e.g. accelerometer and gyroscope). I now want to extract the activity out of it (e.g. walking, standing, driving, ...). I Followed this Jupyter Notebook. But ...
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1answer
28 views

Techniques and semantics in better training of deep learning models

I'm relatively new to Deep Learning, and trying various models and datasets using Keras. I'm starting to love it! Through-out my experimentations, I have come into ...
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1answer
42 views

Classification with deeplearning : clean start vs continue training

I trained some weights to identify apples and oranges (using YOLOv3). If I want to be able to identify peaches, which approach is usually recommended: Start clean and train the 3 classes. Train ...
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1answer
32 views

Semantic issues with predictions made by my trained model

I'm new to Deep Learning. I used Keras and trained a inception_resnet_v2 model for my binary classification application (fire ...

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