Questions tagged [machine-learning]
Questions about computer algorithms that automatically discover patterns in data and make good decisions based on them.
919
questions
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18 views
What are the similarities between Data Science and Machine Learning? [closed]
Recently I took part in an online project about Data Science, I learned some frameworks such as Pandas, Numpy and Sklearn, some basic knowledge, like kNN, Linear Regression, Regularization, Logistic ...
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19 views
How can I express the similarity between a Bing and a Google search result?
I'm working on a "semantic" browser engine where all search engines should look the same. One way to do this is to hard-code parsing rules for each site; another is to use machine-learning. Of course ...
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15 views
On the growth rate of Leela Zero compared to AlphaGoZero
There are not many sources online, but one reference from January says of Leela Zero (LZ) that:
The strength depends on the hardware and on thinking time, but from
the thread "LeelaZero ...
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1answer
34 views
Computer Vision Techniques to find Slope of beach in the 2D Images?
What I am planning to do is to calculate the height and estimate the slope of the segmented Object. The camera will be static and the Object of Interest is the slope of the beach.
I am finding harder ...
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0answers
10 views
Text-to-speech with custom voice
I hope I do not get bashed for such a stupid question, but I'm trying to assess how far are we of a implementation of what I'm about to tell you.
To give a little context, I have this friend that is ...
2
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1answer
16 views
Neural network game players and incremental updates
Neural networks in recent years have been successfully used for gameplaying. A difference between games and e.g. image processing is that the game boards get updated incrementally. Do any neural ...
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2answers
32 views
Why does a RNN network output different based on the training sequence
I've set up an RNN LSTM network in Java using DL4J as the library.
I currently have 500 examples of positive text, and 500 examples of negative text.
When I fitness the training data by first ...
1
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0answers
28 views
Best way to learn Machine Learning after having done a Computer Science Bachelor [closed]
I just graduated from my university with a Computer Science Bachelor.
Because of this, I have good Python knowledge, coded a reinforcement learning AI, did machine learning ABCs with Iris flower ...
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27 views
Computational power of machine learning
In a nut shell, machine learning is a class of algorithms that can "train" data-structures.
You provide a trainer with partial information, and it will produce some entity which can
be queried on ...
2
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0answers
20 views
The No-Free-Lunch Theorem and K-NN consistency
In computational learning, The NFL theorem states that there is no universal learner. For every learning algorithm , there is a distribution that causes the learner to output a hypotesis with a large ...
2
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0answers
22 views
What is the purpose of standardization in machine learning?
I'm just getting started with learning about K-nearest neighbor and am having a hard time understanding why standardization is required. Reading through, I came across a section saying
When ...
1
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1answer
42 views
Are chatbots a good example of overfitting?
In my highschool class we are learning about Artificial Intelligence, and especially the problems that come with machine learning. I was wondering if chatbots like cleverbot were good examples of ...
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15 views
How to transform an arbitrary graph into a fixed vector representation?
Actuality I work in computer vision, specifically on a problem known as "scene graph modeling." This problem aims to convert an image $I$ in a graph $G=(V,E)$ where the nodes $V$ represent the objects ...
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1answer
20 views
How to initialize the first h in an RNN?
Take a Vanilla RNN represented by the function $h_t = f(h_{t-1}, x_t)$, how do you determine $h_0$?
Edit: This answer over on the stats page has helped.
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16 views
Learning the weights in a directed acyclic graph
I have a directed acyclic graph $G=(V,E)$ where each vertex $v$ is associated with a weight $w_v$ such that $$w_v=1+\sum\limits_{(v,v')\in E} w_{v'}$$ and $w_v=1$ in case $v$ is a leaf.
I am trying ...
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18 views
What is the difference between derivative free optimization and derivative optimization in terms of advantages/disadvantages?
I understand the basic operation of the algorithms however i'm unclear as to when to use one over the other and what advantages/disadvantages they offer over each other.
Also as an aside, if anyone ...
1
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1answer
35 views
How to create a model which predicts the radius of a circle? [closed]
My training set is made up of 2d images with one imperfect but broadly circular shape in them (plus plenty of noise). I wish to train a model to predict the "radius" (obviously it's a somewhat ...
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0answers
12 views
Clustering - Complete Linkage draw example
I'm studying unsupervised learning methods (clustering) and i've seen the Complete Linkage Method. I've also seen the following statement:
Unlike single linkage, the complete linkage method can be ...
1
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1answer
27 views
Recover boolean vector from dot products
Question:
I want to determine a boolean vector $b \in \{0,1\}^n$ consisting of zeros and ones, but cannot access it directly. I can only call a black-box computer code which will take the dot product ...
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13 views
Does the weighted max cut problem have applications to machine learning? If so, what are they?
At first, I thought the weighted max cut problem (WMCP) could be of use to binary classifiers, but since the standard WMCP doesn't have any "node groups must be on opposite side of a straight line" ...
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0answers
18 views
CNN Predicting One Class and Accuracy Getting Stuck
My model is a binary classifier.
With the same exact architecture, the model sometimes gets high accuracy (90% etc), other times it predicts only one class (so accuracy is stuck at one number the ...
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0answers
11 views
Model suggestion for detection of malware based on multiple api call sequences
I'm trying to build a RNN (LSTM) model for classification of binary as benign/malware. The data structure I've presently looks as follows
...
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2answers
54 views
What is the official name of a specific type of combination algorithm
Say that I have the following set of variables:
[A,B,C,D,E,F,G,H,I,J,K,L,M,N,O,P,Q,R,S,T,U,V,W,X,Y,Z]
The values represent a list of variables from a dataset. ...
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0answers
22 views
Can Hidden Markov Models be used for real-time analysis?
From what I understand, HMMs construct a underlying sequence of states to maximize the probability of a sequence of observations. As far as I can tell, that should make them inappropriate to use ...
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0answers
18 views
Value flow (and economics) in stacked reinforcement learning systems: agent as reinforcement environment for other agents?
There is evolving notion of stacked reinforcement learning systems, e.g. https://www.ijcai.org/proceedings/2018/0103.pdf - where one RL systems executes actions of the second RL system and it itself ...
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9 views
How would you generate files with several different rules?
Okay, the title is kind of cryptic because I'm lacking terminology (part of the problem).
Situation
Let's say you want to generate data corresponding to one specific, standardized paper document. ...
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0answers
7 views
Query about an equation in GAN-NMT paper
So i was studing the paper Adversarial Neural Machine Translation by Lijun Wu1, Yingce Xia2, Li Zhao3, Fei Tian3, Tao Qin3, Jianhuang Lai1,4 and Tie-Yan Liu.
The link to the paper is : https://arxiv....
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0answers
32 views
How is knowledge of lambda calculus applicable in Computer Science and Machine Learning? [closed]
If I want to do research in computer science and machine learning, is it important to have a well-rounded understanding of lambda calculus?
1
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1answer
26 views
True Error of a binary classifier
For a given classifier h, How is the true error over a distribution D defined?
\begin{align*}
L_D(h) &= \sideset{\mathbb{E}}{}{}_{x,y \sim D} \Pr[h(x) \neq y] \\ &=
\sideset{\mathbb{E}}{}{}_{x,...
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0answers
8 views
Optimising matketing budget on marketing and sales data
I have a dataset from business where the variables include investment across diferent channels and independent variable is the sales.
I have developed a marketing mix model using linear regression to ...
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0answers
14 views
Understanding Multi-headed attention
Recently I came across the concepts like Attention and Transformer architecture. After studying the papers and many blogs, I understood the concepts, but recently one doubt is coming in my mind and ...
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0answers
28 views
Which computational framework lies behind the Chinese “Social Credit System”?
BACKGROUND
The Social Credit System is a data-driven reputation system which draws on several sources to label various entities, namely businesses and individual citizens, with a trustworthiness ...
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0answers
5 views
How do I input (magnitude of) numerical data in CNN/U-net like architectures?
I've been given some (latitudes,longitudes) points with cellular signal strength(float numbers) on those particular points. And I've been given the location, (lat,longs) of cellular towers in a ...
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0answers
27 views
Agnostic PAC learnable hypothesis class for binary classification
I'm trying to prove that any agnostic PAC learnable class $\mathcal{H}$ of binary classifiers is PAC learnable (with respect to the 0-1 loss function), which means that for any density distribution $\...
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0answers
13 views
Is it useful to transform a regression problem into a classification one?
First, I would like to say that I understand the difference between a classification problem and a regression one.
Let's imagine that I'm trying to predict the time of a sprinter to run 100 meters ...
2
votes
1answer
25 views
Learning Specific Topics In Machine Learning [closed]
I am a beginner in machine learning and I already have a good linear algebra/calculus background.
I am interested in being able to eventually understand and implement convolutional neural networks, ...
1
vote
1answer
53 views
Search vs planning in artificial intelligence
I'm studying artificial intelligence following the Russell & Norvig book.
We did a search and planning part that for me is the same (at least on the representation).
I'd like to know what is the ...
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0answers
13 views
How does the Random Forest classification function
I was going the through Random forest classification trying to understand it and I stumbled on two equation and I was wondering if anyone knows their name.
what are the names of the theorms or ...
0
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1answer
33 views
Introduction to computer science for ML [closed]
I have learned python syntax (from books like fluent python or python cookbook etc.) and I want to learn the underlying concepts of computer science (in an abtract way), do you have some books/courses ...
0
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1answer
20 views
Dimension Reduction - Which feature should remove to reduce the dimension of the matrix
Let's suppose that we have the following 2 tables:
If we want to reduce the dimension by one(in every table) which feature we should remove and why ?
I am confused about the way that i should work ...
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0answers
9 views
Is it possible to compute a whole convolution layer at once?
I have an input of 32×32×3 and I want to feed it to a convolution layer that output 32×32×16 feature maps.
I know that I can compute a single feature map as matrix multiplication. But my question is, ...
2
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0answers
21 views
Cross Entropy Function
I've seen two versions of the cross entropy cost function, and conflicting information about it.
\begin{equation}J(\theta) = -\frac{1}{N} \sum_{n=1}^N\sum_{i=1}^C y_{ni}\log \hat{y}_{n_i} (\theta)\end{...
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0answers
8 views
Simple Question About the Nature of Supervised Learning Predictive Models in Relation to their Training Data
Would a deployed or deployment-ready (i.e., already-trained) supervised learning model have a 100% accuracy rate for predictions on the training data (if you were to run the training data through it ...
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0answers
5 views
Is there any intersection in the applications of multi-agent reinforcement learning and more traditional branches of machine learning?
From my limited understanding, it seems like the structure of problems that multi agent reinforcement learning attempts to attack is quite different from the structure of problems in more traditional ...
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0answers
11 views
Linear regression: not noramalising by y's norm
I was recently reading an article on Pearson correlation, and OLS coefficients. I came across the following section.
Finally, these are all related to the coefficient in a one-variable
linear ...
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0answers
42 views
What is the best algorithm known to learn the regular expression from a set of positive examples?
I have a blackbox program that generates a set of strings. What is the best regular expression learner that I can use to learn (approximate) what the blackbox program uses as a generator? Note that I ...
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0answers
15 views
maximum tensor rank for computer vision tasks
Most computer vision tasks do not require 4+ ranked tensors.
Are there any use cases for tensors with ranks more than 4 in computer vision? Are there any use cases for deep learning in general?
1
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1answer
27 views
Prior probability in HMM
This is the HMM model considered in the question
And this is the emission probabilities for the respective states. There are two emission values, bringing an umbrella and not bringing an umbrella.
...
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0answers
15 views
how can i find that the size of tree which is built by C5.0 algorithm is good?
I built C5.0 for balancing data with 16 attributes. and the size of my model is 125 and it used 15 attributes for building model.how can i find the size is good?
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25 views
Question about implementing GAN(Generative Adversial network)?
so most examples I've seen create two NN-s, train them, then they stack them, make the discriminator part untrainable and then train this stacked NN, why do we do this? So loss, that is calculated on ...
