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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184 views

Can anybody explain such behavior of accuracy and loss of my Net(caffe)?

I used this project for example(framework - caffe, arhitecture of net - mod of AlexNet, 400 images are used for training). I have this result: or this: Solver: ...
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71 views

Advanced NLG - robot journalist

I want to produce a bot in Python that automatically generates short football summaries from Whoscored data. For my first stage I generate the articles with different sentence templates and lots of ...
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332 views

CNN attention maps on non-images

My datasets are not actual images, so using methods with ImageDataGenerator or pre-trained networks might not apply in this case. Data Structure: Each "image" is a 2048-long vector that has float ...
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106 views

Train, Validation and Test Split for Reporting Accuracy of Neural Model and BOW

I need to report accuracies of my neural model in a conference paper as compared to various baselines. What are the accepted standards for reporting accuracies in a fair manner? Neural Model: To be ...
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0answers
67 views

seq2seq vector to letters model

I'm looking to build a sequence-to-sequence model that takes in a 2048-long vector of 1s and 0s as my input and translating it to my known output of (a variable length) 1-20 long characters (ex. ...
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1answer
209 views

How could the “AI in a box experiment” work IRL?

If an AI was trapped in a box, as posited in this thought experiment, could it really convince a person to let it out? What motives would it have? Freedom? Why would an AI want freedom? What ...
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1answer
63 views

How do I classify an image that contains only polygons?

I have two closed polygons, drawn as connected straight black lines on a white background. I need to classify such images in to three forms Two separate polygons One polygon encloses the other The ...
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2answers
114 views

Why is MSE used over other quadratic loss functions?

So I was wondering, why I have only encountered square loss function also known as MSE. The only nice property of MSE I am so far aware of is its convex nature. But then all equations of the form $x^{...
2
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1answer
116 views

possible to train some model to recognize trash?

I want to build a semi autonomous robot/machine that will clean up trash in cities. For this to be possible it needs to recognize 'trash'. As trash can be all sorts of things (think ciggaret buts, ...
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3answers
329 views

Are expert systems dead?

Besides all the fashion about machine learning, data analysis and reinforcement learning, what is going on in the expert systems field and symbolic AI ? There are plenty of domains where machine ...
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10 views

Lego minifigure facial recognition: where to start?

I'm interested in starting a project that will identify the face of a Lego minifigure from a digital photo. I eventually want to do a "face swap," but I'd like to start with the challenge of ...
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28 views

How is clustering used in the unsupervised training of a neural network?

How is clustering used in the unsupervised training of a neural network? Can you provide an example?
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14 views

A problem about the relation between 1-oracle and 2-oracle PAC model

This problem is about two-oracle variant of the PAC model. Assume that positive and negative examples are now drawn from two separate distributions $\mathcal{D}_{+}$ and $\mathcal{D}_{-} .$ For an ...
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18 views

Is there any paper that uses truncated neural networks?

Recently, I've found good success in truncated neural networks ie functions of the form $$ g=f1_{[-M,M]^d}, $$ where $f:\mathbb{R}^d\to\mathbb{R}^n$ is a feed-forward neural network and $1_{[-M,M]^d}$ ...
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16 views

Training dataset for convolutional neural network classification - will images captured on the ground be useful for training aerial imagery?

I am an agronomy graduate student looking to classify crops from weeds using convolutional neural networks (CNNs). The basic idea that I am wanting to get into involves separating crops from weeds ...
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25 views

How can I match numbers with expressions?

Let's say I have the number 123.45 and the expression one hundred twenty-three and forty-five cents. Can I develop AI to identify these two values as a match? If I can, how should I do that?
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17 views

Find the nearest object in a image which is captured from camera?

Objective : To find the nearest object (closer distance object) in the single camera image. But Image Contains multiple objects shown below: I searched in the net and found this formula to ...
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16 views

Flattened vector observation or convolutional neural network input?

This is more of a general question of how to model/preprocess 'visual' state-observations to an Agent in Reinforcement Learning that I'll illustrate with an example. Say you have a reinforcement ...
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38 views

Reinforcement learning possible with big action space?

I’m experimenting with reinforcement learning for a 2D pixel plotting task, and am running into an issue that (I think) has to do with the big action space. It goes like this: The Agent gets two ...
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12 views

How are data assimilation and machine learning different?

This might seem like a really silly question, however I have not been able to find any answers to it on the internet. From my rough understanding of data assimilation, it combines data with ...
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0answers
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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41 views

How can I recognise the name of a molecule given an image of its structure?

I want to recognize the name of the chemical structure from the image of the chemical structure. For example, in the image below, it is a benzene structure, and I want to recognize that it is benzene ...
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16 views

Is CNN capable of extracting the descriptive statistics features

I was trying to build a CNN model. I used time series data of daily temperature to predict if there is risk of an event, say bacteria growth. I calculated the descriptive statistics of the time series,...
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14 views

Need to analyze input CSV files and determine whether input file is good or bad w.r.t it's data

We have a scenario where we need to implement an Artificial Intelligence solution which will evaluate the input data file of my Azure Data Factory pipeline and let us know whether the file is good or ...
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56 views

Finding the right model

Let us say that i have two ball throwing machines which has some algorithm running in the back-end for releasing the balls. One machine shows it throws 5 balls in 1 sec. Other shows the exact ...
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0answers
33 views

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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32 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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0answers
18 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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30 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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22 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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0answers
20 views

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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21 views

How would the “best function” been constructed if there are no computationally limitations?

I am reading the Wikipedia article on gradient boosting. There is written: Unfortunately, choosing the best function $h$ at each step for an arbitrary loss function $L$ is a computationally ...
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22 views

Keyword spotting with custom keywords and why not use speech recognition instead

My question regards performing keyword spotting for custom keywords and justifying the use of keyword spotting models instead of speech recognition. I have been doing some searching around Keyword ...
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1answer
16 views

Deep audio fingerprinting for word search

Simply speaking, I'm trying to somehow search an audio clip for a list of words, and if found, I mark the time stamps. My use-case is profanity check with a list of pre-defined profane words. Is ...
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9 views

Is there any time-varying directed graph dataset?

I am interested in the node classification task for graph data. So far,I've tried it with the Cora dataset, but it is an undirected graph and has word attributes as features. I want to extend this ...
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31 views

Understanding the partial derivative with respect to the weight matrix and bias

Say we have the layer $X W + b = Y$. I want to get $\frac{dL}{dW}$ and we assume I have $\frac{dL}{dY}$. So all I need is to find $\frac{dY}{dW}$. I know that it should be $X^T\frac{dL}{dY}$ but don'...
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34 views

Showing machine learning results to Group CEO

I am working as a Data Scientist in a non IT company(in fortune 500) and the group CEO is visiting the Data Science department after it's inception a few months back. We have models like chrun ...
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1answer
30 views

Prove that in such cases, it is possible to find an ERM hypothesis for $H_n$ in the unrealizable case in time $O(mnm^{O(n)})$

Let $H_1$ , $H_2$ ,... be a sequence of hypothesis classes for binary classification. Assume that there is a learning algorithm that implements the ERM rule in the realizable case such that the ...
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1answer
55 views

“Outside-in” versus “Inside-out” machine learning

A little background... I’ve been on-and-off learning about data science for around a year or so, however, I started thinking about artificial intelligence a few years ago. I have a cursory ...
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34 views

Intelligent reflecting surface

I wanted to know about Intelligent reflecting surface (IRS) technology. what is the application of IRS in wireless communication? what are the competitive advantages over existing technologies?
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66 views

Threshold selection for Siamese network hyper-parameter tuning

I'm interested in modeling a Siamese network for facial verification. I've already written a simple working model that inputs feature vectors generated from two CNNs with shared weights then outputs a ...
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0answers
31 views

why the sigmoid function will be 1 and 0 if we use a fully connected layer that produce a big enough positive(res negative )output

HI I am using a fully connected network that uses sigmoid if we feed a a big enough weights the sigmoid function will finally become 1 or 0 , is there any solution to avoid this ? and will this lead ...
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0answers
21 views

Which AI algorithm is great for mapping between two XML files

My work colleague got a project with a lot of work that is not hard or complicated. The problem is simple but it is a lot of work. We have two XML files with a lot of variables in it. Not only is ...
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0answers
15 views

Applying ML algorithms to data-sets with similar meta-features?

Is there any grounds for assuming an algorithms applied to a data-set that created a decently accurate model will perform as well on a different data-set with meta-features chosen and evaluated by ...
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0answers
26 views

How to implement fisherface algorithm and how much time will it take?

I found on the web that fisherface is the best algorithm for face detection. Before investing deeply into it, I just want to know how hard is it to implement it and how much time will it take. I am ...
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7 views

How to use machine learning to create combine of opposite images side by side

Inspired by: Two Worlds Pictures I just want to create a Machine Learning Model that can automatically combine the opposite images into 1 image. I am thinking about 2 possible solutions: Pose ...
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0answers
8 views

Mobile App Recommendation: How to get the rate of a specific user submit for a specific application

I have a mobile app recommendation project, so I need data set which has user-app matrix-rate. Actually, I want to know what rate does a specific user submit for a specific application. in other words,...
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0answers
49 views

How to train and update weights of filters

I have some problems with training CNN :( For example: Input 6x6x3, 1 core 3x3x3, output = 4x4x1 => pool: 2x2x1 By backpropagation I calculated deltas for output. This tutor and other tutors are ...
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0answers
15 views

How do I recover the 3D structure of a layer after a fully-connected layer?

I want to implement a CNN, but I want to explore what happens when my first layer is a fully-connected one. I still want to use convolutions, of course, but I want to apply them after the first layer. ...
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1answer
19 views

When a linear discriminant could give excellent or possibly even the optimal classification accurcy?

I am actually reading the linear classification. There is a question in the question set behind the chapter in the book as follows: Sketch two multimodal distributions for which a linear discriminant ...