Questions tagged [machine-learning]

For questions related to machine learning (ML), which is a set of methods that can automatically detect patterns in data, and then use the uncovered patterns to predict future data, or to perform other kinds of decision making under uncertainty (such as planning how to collect more data). ML is usually divided into supervised, unsupervised and reinforcement learning. Deep learning is a subfield of ML that uses deep artificial neural networks.

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Object detection won't train after first step

I was trying to build an object detection model but when I try to train the model, it gets stuck after the first step. I attached the screenshot of the screen. I left it on overnight and it won't go ...
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DQN, how to choose the reward fucntion?

I built a simple AI system that tries to solve the 8 puzzle using DQN. The problem is, if the agent gets only a reward greater than zero when winning, the training will take a long time, so I made a ...
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What is the difference between game theory and machine learning?

What is the difference between game theory and machine learning? I had gone through the papers Deep Learning for Predicting Human Strategic Behavior, by Jason Hartford et al., and When Machine ...
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What topics lie at the cutting edge in the following areas? [closed]

I am trying to get an idea of the topics and challenges that lie on the cutting edge of any of the following areas: (1) machine learning and probabilistic inference - such as graphical models, kernel ...
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1answer
43 views

Which csv data sets can test ability of machine learning and deep learning? [closed]

From easy to difficult , which csv data sets can test ability of learning algorithm? I find circular curl into inside Where can download these data sets?
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1answer
38 views

Can a trained object detection model deal with variations of the input?

Suppose an object detection algorithm is good at detecting objects and people when an object and person is close to a camera and upright. If the person walks farther away from the camera and is "...
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1answer
47 views

Need examples for the following definitions

I am currently reading the paper "Similarity of Narratives" by Loizos Michael (link below) and I am having a hard time figuring out the definitions listed (p.107 - p.109). Could someone please give ...
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2answers
37 views

Building an AI that generates text by itself

Now I know this might break some StackExchange rules and I am definitely open for taking the thread down if it does! I am trying to build an AI that can write it's own book and I have no idea where to ...
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39 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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44 views

Finding the right model [closed]

I am searching for an apt supervised model for the following use case: If I have a sum (say 10) and it can be distributed in a predefined number of bins (say 5) in a number of ways for instance: ...
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1answer
39 views

How to detect any native language when written in Latin characters?

Assume somebody knows only to write in Latin characters. If they write words of any other language (example: Hindi, French, Latin) using the Latin alphabet, how can I detect that language? Example: ...
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Is there an audio dataset with the corresponding phonemes in the audio?

I am looking for a dataset of clear audio, a corresponding transcript (optional), and most importantly a list of all the phonemes said in the audio, with the length of each phoneme and a mention of ...
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How to perform regression with multiple numeric (positive and negative) inputs and one numeric output?

I have a dataset with different types of numerical values (both negative and positive numerical values) for the inputs (for example, -40, -35, 1, 25, 39, etc., that is, multiple inputs) and single ...
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1answer
54 views

Eligibility vector for softmax policy with policy gradients

There is this nice result for policy gradients that the gradient of some performance measure, $\nabla v_{\pi_{\theta}}(s_0)$ (here, in the episodic case for the starting state $s_0$ and policy $\pi$, ...
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Correlating two models to predict the output of one that corresponds to an output of the other

I am currently working on a problem and now got stuck to implement one of it's steps. This is a simple attempt to explain what I am currently facing, which is something that I am aiming to implement ...
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1answer
26 views

Is it possible to use AI for detecting the volume of a cup

I was just wondering if it's possible to use Machine Learning to train a model from a dataset of images of cups with a given volume in the image and then use object detection to detect other cups and ...
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27 views

Is logistic regression used for unconstrained or constrained optimisation problems?

Is logistic regression used for unconstrained or constrained optimization problems, and why?
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29 views

Does CNN Model accuracy increase if I fit it twice

As I train my CNN model I realised that fitting model twice, ie. running again this code ...
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1answer
30 views

Relationship between training accuracy and validation accuracy

During model training, I noticed various behaviour in between training and validation accuracy. I understand that 'The training set is used to train the model, while the validation set is only used to ...
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0answers
35 views

Can learned feature vectors be considered a good encryption?

Considering I have some neural network that, using supervised learning, transforms a string into a learned feature vector where "close" strings will result into more close vectors. I know that since ...
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30 views

What ML algorithms would you suggest in fraud detection?

There are a lot of ML algorithms suggested for fraud detection. Now, I have not been able to find a general overview for all of them. My goal is to create this overview. What algorithms would you ...
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1answer
37 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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34 views

Drug Review dataset - approach [closed]

I am trying to experiment using the Drug Review open dataset https://archive.ics.uci.edu/ml/datasets/Drug+Review+Dataset+%28Drugs.com%29 I need to answer questions from a domain perspective, such ...
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1answer
62 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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3answers
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Prerequisites for Andrew Ng's Machine Learning Course [closed]

I am planning to enroll for Andrew Ng's Machine Learning course https://www.coursera.org/learn/machine-learning. I've no background in math. Is it OK if I start the course and learn math as and when ...
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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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Why would the application of kernelization prevent underfitting

"Why would the application of kernelization prevent underfitting" I read in some paper that applying kernelization would prevent you from underfitting. Why is that? Source: http://www.cs.cornell.edu/...
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Which algorithm and architecture to use for 1:1 matrix transformation of an 8X8 dimension?

I would like to map the simplest 8X8 matrices, one to one, but am not sure which AI algorithm would give the best performance. I am thinking about the DeepLearning4j, however, I don't know which ...
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28 views

Interpretability of feature weights from Gaussian process classifier

Suppose I trained a Gaussian process classifier with a linear kernel (using GPML toolbox) and got some feature weights for each input feature. My question is then: Does it/When does it make sense ...
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2answers
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What is probability distribution in machine learning?

If we were learning or working in machine learning field then we frequently come across this term probability distribution. I know what probability, conditional probability and probability ...
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29 views

Difference in the code structure of RNN and CNN

I understand that in general RNN is good for time series data and CNN image data, and have noticed many blogs explaining the ...
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1answer
24 views

Can non-sequential deep learning models outperform sequential models in time series forecasting?

Can a CNN (or other non-sequential deep learning models) outperform LSTM (or other sequential models) in time series data? I know this question is not very specific, but I experienced this when ...
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34 views

Can supervised learning be used to solve the inverted pendulum problem?

I know that reinforcement learning has been used to solve the inverted pendulum problem. Can supervised learning be used to solve the inverted pendulum problem? For example, there could be an ...
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3answers
89 views

How do you interpret this learning curve?

Loss is MSE; orange is validation loss, blue training loss. The task is NN regression (18 inputs, 2 outputs), one layer 300 hidden units. Tuning the lr, mom, l2 regularization parameters this is the ...
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1answer
28 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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What are examples of models for traffic sign detection that can be easily implemented?

I'm working on a college project about traffic sign detection and I have to choose a paper to implement it, but I have basic knowledge of TensorFlow and I'm afraid of choosing a paper that I can't ...
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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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0answers
13 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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2answers
46 views

Oposite type of predictions for unbalanced dataset

I have a big dataset (28354359 rows) that has some blood values as features (11 features) and the label or outcome variable that tells whether a patient has a virus caused by a Neoplasm or not. The ...
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1answer
39 views

What is the difference between Kaldi and DeepSpeech speech recognition systems in their approach?

I would like to know how do Kaldi and DeepSpeech speech recognition systems differ algorithmically? Which one would be more accurate for continuous speech in time?
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1answer
45 views

What is the relationship between robustness and adversarial machine learning?

I have been reading a lot of articles on adversarial machine learning and there are mentions of "best practices for robust machine learning". A specific example of this would be when there are ...
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Is this TensorFlow implementation of partial derivative of the cost with respect to the bias correct?

I have a neural network for MNIST classification which I am hard coding using TensorFlow 2.0. The neural network has an input layer consisting of 784 neurons (28 * 28), one hidden layer having "...
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2answers
65 views

What is the difference between a learning algorithm and a hypothesis?

What's the distinction between a learning algorithm $A$ and a hypothesis $f$? I'm looking for a few concrete examples, if possible. From what I understand, one way to vary the hypothesis $f$ would be ...
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How can an AI train itself if no one is telling it if its answer is correct or wrong?

I am a programmer but not in the field of AI. A question constantly confuses me is that how can an AI be trained if we human beings are not telling it its calculation is correct? For example, news ...
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0answers
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Are there any easy ways to create annotated training images for object detection?

For the purposes of object detection, are there any easy ways to create annotated training images? For example, if we have $10,000$ images and want to draw bounding boxes on 2 objects for each image, ...
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1answer
58 views

How does the decision tree implicitly do feature selection?

I was talking with an ex-fellow worker and he told me that the decision tree implicitly applies a feature selection. He told me that the most important feature is higher in the tree because of the ...
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Why do Bayesian algorithms work well with small datasets?

I read very often that Bayesian algorithms work well on small datasets. Why is that? I think it is because they might generalize more, but why is that? See also Investigating the use of Bayesian ...
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1answer
64 views

Are there any public real-life code examples of ML applications in Python?

Problems I often face at work usually differ from tutorial or book-like examples so I end up with a code that works but it's not elegant and takes too much time to write. I wanted to ask you if there ...
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1answer
126 views

Should I train different models for detecting subsets of objects?

Suppose we have $1000$ products that we want to detect. For each of these products, we have $500$ training images/annotations. Thus we have $500,000$ training images/associated annotations. If we want ...
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0answers
19 views

Troubleshooting Binary Classifier

I trained a binary classifier using ML.NET's AutoML feature on a small dataset (compared to other, similar models I've trained that seem to work well)-around 500 rows with around 50 features. AutoML ...