Questions tagged [machine-learning]
Questions about computer algorithms that automatically discover patterns in data and make good decisions based on them.
973
questions
3
votes
2answers
75 views
Being stuck and frustrated with my masters project
I'm doing a masters in CS that requires me to implement from scratch most of the neural network models and because python libraries aren't applicable to what i want.
The problem is that i don't feel ...
0
votes
0answers
12 views
Sckit regression on power set of data [closed]
How do I run linear regression on every subset of dataframe in a loop with Linear Regression of scikit-learn?
...
0
votes
0answers
10 views
How does the BERT model (in Tensorflow or Paddle-paddle frameworks) relate to nodes of the underlying neural-net that's being trained?
The BERT model in frameworks like TensorFlow/Paddle-paddle shows various kinds of computation nodes (like subtract, accumulate, add, mult etc) in a graph like form in 12 layers.
But this graph doesn'...
1
vote
0answers
13 views
Clustering customer with string data
I'm looking for a customer clustering solution. I have done a lot of research on the machine learning level to find algorithms that could fit my needs but I can't find much information when the data ...
0
votes
0answers
14 views
Exploding gradients problem in gradient descent in multi-output ridge regression setting [closed]
Multi-output ridge regression:
$W^{*}=\underset{W}{\arg \min } \frac{1}{\mathcal{N}}\|Y-WX\|_{F}^{2}+\lambda\|W\|_{F}^{2}$
There are $Q$ outputs, $N$ samples, and $P$ covariates (features).
$\hat{Y}...
2
votes
3answers
534 views
Support Vector Machines as Neural Nets?
This is more of a conceptual question.
I have learned about Neural Nets, and I have some clue as to how Support Vector Machines work. I read somewhere however that given the appropriate kernel (is ...
0
votes
1answer
66 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 ...
1
vote
1answer
28 views
Asymptotic analysis for machine learning algorithms
I wanted to know if it would practical and useful to analyse machine learning algorithms in terms of asymptotic computational complexity.
I have noticed this is very uncommon. However, I believe it ...
0
votes
0answers
14 views
Weights vs Training ML
The weights of Machine Learning models are learned during the training process. Why is said that the higher values of weights leads to the overfitting of the model? Why is it necessary to have low ...
2
votes
0answers
14 views
Energy consumption off CNN models
I want to calculate/estimate the energy consumption for the different convolutional neural networks. Is there any possibility to measure the energy consumed by AlexNet for example with a tool or with ...
0
votes
1answer
18 views
Mapping categorical data in K-nearest neighbour
I have a data set which contains categorical data, for example:
...
0
votes
0answers
19 views
Why does my EM algorithm not converge?
Any ideas why my likelihood probability for this EM algorithm doesn't converge (have slope of 0) to "find" the three clusters? I've tried increasing the iterations, which makes the slope nearly ...
1
vote
0answers
14 views
Which machine learning should I choose for a one->list relation
I'm trying to write machine learning software that will predict a list of 3 values from a given number input (reverse grayscale). There is a function determining values of the list to the grayscale, ...
0
votes
1answer
141 views
Pac learnable when changing distribution
if H is Pac learnable according to
Definition 3.1 (PAC Learnability) A hypothesis class H is PAC learnable
if there exist a function $m_H\colon(0,1)^2 \mapsto N$ and a learning algorithm with the
...
3
votes
1answer
151 views
Measures of performance in machine learning
I'm new to machine learning and struggle to interpret the results I get from different measures of performance. If for several prediction models I have e.g. accuracy, precision, recall, F1, FPR, and ...
1
vote
1answer
31 views
What kind of bigram probability smoothing is this?
I hope it isn't off topic but I need to understand this example. Given the corpus 12 1 13 12 15 234 2526 and smoothing factor of ...
2
votes
2answers
30 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 ...
0
votes
1answer
12 views
Confused on Variational AutoEncoder
I'm a bit confused on how Variational Autoencoders are trained. In particular I'm confused on how the latent variable is generated for each input.
My questions are as follows:
When running ...
0
votes
0answers
11 views
Relationship between keystroke pattern and emotion
There are API provided by Google and Microsoft that takes as input the image of a person and output a probability distribution of the person's mood. I'm wondering if there an API that can take as ...
4
votes
2answers
636 views
Mathematical proof for why gradient descent algorithm always converges
I am currently learning machine learning and I stumbled across gradient descent. I understand why the algorithm always converges to the global/local minimum when the learning rate is small enough in ...
0
votes
1answer
49 views
Weighting function for Non Uniform Learning
Consider a hypothesis class $H = \cup_{n=1}^{\infty} H_n$, where for every $n\in N$, $H_n$ is finite. Find a weighting function $w : H ->[0, 1]$ such that $\sum_{h \in H} w(h) ≤ 1$ and so that for ...
0
votes
0answers
14 views
What is the main concept of using lexical,linguistic, semantic or syntactic approach in NLP for cyberbullying
Am really in need of some explanation, am working on a nlp cyberbullying detection tool which i will deploy to the web using django framework, however, am stuck on some idea, can someone explain to me....
1
vote
0answers
39 views
Can anyone think of applications of a 3 way (k-way) dot product in computer science or data mining
I have developed a locality sensitive hashing algorithm for the 3-way or k-way dot product. When I say 3-way dot product I mean the following. Suppose we have
$x,y,z \in [-1,1]^{S}$ for $S \in \...
0
votes
1answer
18 views
Using a point as an input for a perceptron
Can a point be used as the input for a perceptron/neural net?
The relationship between the two numbers that make up a 2D point does not affect the output, but does this not matter when the ...
0
votes
2answers
63 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. ...
0
votes
0answers
20 views
Image classification with zero data
Given an image of a biology diagram, I would like to classify the diagram into these 4 categories:
Plant
Animal
Cell
Anatomy
However, I don't have any training data. I would like to avoid the ...
1
vote
2answers
2k views
Effect of value of k in K-Nearest Neighbor
In K-Nearest Neighbor the value of k decides the accuracy of classification. What are the pros and cons of choosing smaller value for k and larger value for k?
0
votes
1answer
755 views
Condensed Nearest Neighbor Explanation
I have a question regarding the Condensed Nearest Neighbor algorithm from ...
0
votes
0answers
16 views
Propositional setting VS relational setting
I came across "propositional setting" and "relational setting" in this paper.
I don't know what the author means.
What's the difference between "propositional setting" and "relational setting" in ...
0
votes
0answers
78 views
vc dimension of binary decision trees of depth d?
how do i find the vc dimension of the hypothesis space H ,of the binary decision trees of depth d-2?
will the hypothesis space H consist of{0,1} and the vc dimension is the number of ways in which we ...
1
vote
1answer
34 views
Interactions between predictive analytics, ML, and case-based and rules-based reasoning
For my studies on economy, I work on prediction of judicial decisions. I don't really understand the interactions between several concepts:
predictive analytics
machine learning
case-based reasoning
...
0
votes
1answer
117 views
How can I represent a set of graphs for learning purposes?
I have a network of labelled digraphs and a I need to perform a unsupervised learning algorithm on this data.
I am interested in embedding a network of description logic documents in a vector space ...
0
votes
1answer
59 views
How can we get small test error reducing only train error?
My question is about mathematical part of machine learning algorithms, especially about using it in neural networks. We train network reducing train error and I was thinking about how then test error ...
0
votes
0answers
11 views
How to set width and depth of an attractor in hopfield network?
As far as I know hopfield network stores patterns as it's attractor states. But the width and depth of basins of attraction is not determined by user. Is it possible to make hopfield network to set ...
0
votes
1answer
38 views
Classification accuracy based on top 3 most likely classifications
My goal is to recommend jobs to job seekers based on their skill set.
Currently I'm using an SVM for this, which is outputting one prediction, e.g. "software engineer at Microsoft". However, consider ...
5
votes
2answers
208 views
Why does the effectiveness of my reinforcement based neural network recede after a while?
I have a reinforcement based neural network training on the OpenAI gym CartPole-v1 environment. For the structure and training algorithm, assume it is the same as the one in this article.
Typically, ...
0
votes
0answers
16 views
Training a model from self-play
Say I'd like to build a Go AI. The Go AI takes in the board state and then predicts who's more likely to win from that state. When I want to make a move, I just test every next board state I could ...
0
votes
1answer
97 views
How to find max margin for non-separable SVM?
I am new to Machine Learning. Suppose a training set of positive (square) and negative (circle) points is given like:
Obviously there would be no nice linear separator of positive and negative points....
0
votes
0answers
21 views
Using The Output Of Semantic Segmentation In Autonomous Driving
I have read a couple of papers on semantic segmentation and ran this github code (which was trained on Cityscapes) against a KITTI sample image and it did pretty well (as seen below).
I get that ...
1
vote
1answer
33 views
Text detection in computer vision
I'm curious about the way text recognition works in machine learning(or more generally, the question of object vs not object) in computer vision.
How are systems trained when the not-object data set ...
0
votes
0answers
14 views
Path planning agent in a grid with compulsory states to visit with Reinforcement Learning
Is it possible to make a Reinforcement Learning agent for path planning in a 2D grid where visiting certain intermediate states is mandatory?
Please give an insight if it is indeed possible as to ...
0
votes
2answers
43 views
Interpolation: How to generate 3D objects from 2D cross-sections?
Consider a sphere sitting on an $xy$-plane, and take 2D slices parallel to the $xy$-plane at various heights of z. Suppose we take 10 slices, evenly spaced along the $z$-axis, and now have 10 images ...
0
votes
1answer
33 views
How do we fix area of detectors in object detection?
I have gone through various articles on medium and also some from other sites trying to understand SSD. I am able to figure out most of the things from articles except this one.
They always say that ...
2
votes
0answers
28 views
How to use machine learning algorithm for different input data? [closed]
Yes, You heard it right. My title is "How to use a machine learning algorithm for different input data?",
For example, we have an algorithm called "Email spams detector". Okay, so how to apply the ...
0
votes
2answers
328 views
What are the drawbacks of Normalized Mutual Information clustering evaluation method?
What are the drawbacks of Normalized Mutual Information (NMI) clustering evaluation method?
For evaluating what clustering algorithms, is the NMI evaluation method suitable?
0
votes
1answer
55 views
Why the negative reward function in linear quadratic regulation encourage to be at original state?
I was reading Stanford's CS 229 materials on Linear Quadratic Regulation ( Lecture note 13, youtube Lecture 18, around time 36 min).
And it mentions that:
" the quadratic formulation of the reward is ...
6
votes
1answer
411 views
Machine learning approach to auction game
I am newbie with machine learning. In order to learn more I decided to try solving a specific problem/game that I have in mind. The problem is the following:
I have a list of $N$ items which are ...
0
votes
0answers
9 views
In Markov Decision Processes, why does R0 get skipped?
I'm in the process of learning the MDP, and a pretty small thing is bugging me. Everywhere I look, I see the order of things go in this order:
$S_{0}, A_{0}, R_{1}, S_{1}, A_{1}, R_{2}, \ldots, A_{t},...
1
vote
1answer
67 views
Do data points mean Eigenfaces in higher dimensional space?
I saw the following animation at making sense of PCA
, which shows blue data points.
I am reading a paper on Eigenfaces which says that:
"a typical image of size 256 by 256 becomes a vector of ...
4
votes
1answer
246 views
reinforcement learning in gridworld with subgoals
Andrew Ng, Daishi Harada, Stuart Russell published a conference paper entitled Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping.
There is a specific example ...
