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Questions tagged [machine-learning]

Machine learning algorithms build a model of the training data. The term "machine learning" is vaguely defined; it includes what is also called statistical learning, reinforcement learning, unsupervised learning, etc. ALWAYS ADD A MORE SPECIFIC TAG.

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20 views

Box-Cox Transformation does not normalize data sufficiently sometimes

initially as far as I have dug up on internet and books I have seen that Box-Cox transformation may not normalize data as we wish. Besides, log-likelihood function is maximised with $\lambda$ variable ...
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21 views

What is the slowest day at Six Flags? [on hold]

Where could I find a chart or almanac on ticket sales for Six Flags over Georgia to go with the family on line less days?
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17 views

How can we call likelihood function a joint PDF when the individual terms do not represent Probabilty

My understanding of the Probabilty Density Function is that they evaluate to 0 at a particular point . So if we have some i.i.d points $x_{n}$ from a Normal distribution and we write : \begin{equation}...
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21 views

why scikit-learn is so disgustingly overfitting? [on hold]

I bumped into a problem that dazzles me very much, I can't believe it's actually happening. I trained an elastic net using last version of scikit-learn function ElasticNetCV and a 4 folds CV repeated ...
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0answers
12 views

Coding Random Forrest in R [on hold]

I'm looking to code a random forest in R but am having a bit of trouble in my dataset. Before I get into the problem, let me reproduce my code below. The response variable of interest is '...
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19 views

Understanding backprop equations

I was watching a video on backprop from deeplearning.ai where one particular thing confused me a lot. In the backprop, as shown below, Why aren't we averaging <...
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4 views

Approximate Bayesian Computation: Applications to Elevator Group Control Systems

I am working on a project where I will be using Approximate Bayesian Computation (Likelihood-Free Inference) in order to improve an Elevator Group Control System, e.g. minimize the waiting time of the ...
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0answers
16 views

How do you define the error in a hidden layer of a neural network?

I am reading some introductory texts on neural networks. While I am able to understand that the error in the final layer of the neural network is but I am not able to understand how the errors in ...
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6 views

Having trouble figuring out how loss was calculated for SQuAD task in BERT paper

The BERT Paper https://arxiv.org/pdf/1810.04805.pdf Section 4.2 covers the SQuAD training. So from my understanding, there are two extra parameters trained, they are two vectors with the same ...
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1answer
18 views

How to use convolutions of pictures instead of FC layers? [on hold]

How to use convolutions of pictures instead of FC layers? How can i do this effectively and efficiently.
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19 views

Logistic Regression - Coefficients not defined because of singularities

I am running a regression model to predict dropout from an online program. People have to take 5 classes but some people dropped before taking the 5 courses. So I am using a dummy variables that is 1 ...
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0answers
7 views

How to get top features that contribute to anomalies in Isolation forest

I am using Isolation forest for anomaly detection on multidimensional data. The algorithm is detecting anomalous records with good accuracy. Apart from detecting anomalous records I also need to find ...
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7 views

Cost function increases dramatically at first then starts decreasing

I am training a simple linear regression algorithm using stochastic gradient descent. When plotting cost (MSE) vs number of iterations I get a plot which looks very strange: What would be the ...
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7 views

Changing the regression problem to a classification problem

I'd like to do the classification on a crime data around the country. However, what I have for the label is the crime coefficient which is from 0 to 1. I'd like to make up some interval like 0~0.3 as ...
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13 views

Are there any other image classification methods besides using neural networks?

When reading about image classification, the only occurring terms are "neural networks", "deep learning" and "CNN". It seems like there are no other methods for this task. I have worked with neural ...
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14 views

Deviance when y = 0

I am trying to compute deviance for the predictions of my dataset and I encounter quite a big problem here. Deviance is calculated as : $2 (\log(\mathrm{yTrue}) - \log(\mathrm{yPred}))$ where $\log$...
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9 views

Normalising predictions across datasets

I am currently training a model to predict a binary attribute. The model gives the output in range [0, 1]. The metric is TPR@FPR, e.g. I need to achieve maximum ...
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0answers
34 views

Bias Variance Decomposition 2.7 in Elements of Statistical Inference

I try to derive 2.7 from the book. I expose my demonstration $E_\tau[(y_0-\hat{y}_0)^2]=E_\tau[y_0^2]-2E_{\tau}[y_{0}\hat{y_{0}}]+E_{\tau}[\hat{y_{0}}^{2}]$ $= y_{...
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0answers
6 views

Why different seeds produce different mse values for regression tree and ols?

I compare regression tree and ols in terms of out of sample prediction. I realized that the mse values changed when i change the seeds before getting train and test set. Sometimes ols is better ...
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1answer
39 views

How do I implement stochastic gradient descent correctly?

I'm trying to implement stochastic gradient descent in MATLAB however I am not seeing any convergence. Mini-batch gradient descent worked as expected so I think that the cost function and gradient ...
3
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1answer
52 views

How to plot logistic decision boundary?

I am running logistic regression on a small dataset which looks like this: After implementing gradient descent and the cost function, I am getting a 100% accuracy in the prediction stage, However I ...
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0answers
13 views

XOR Neural Network, Problem finding shapes of delta for backpropagation algorithm

I am taking the Machine Learning course by Andrew Ng on coursera. I am trying to make a neural network learn to do XOR, but I am facing a problem regarding the shapes of the $\delta$ vectors, and $\...
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0answers
9 views

Best Machine Learning Algorithm for Grouping Similar Census/Survey [on hold]

I am working in a company which have many census/survey. The problem is there are so many census/survey that have similar questionnaire variable which made many of our census/survey seems to be ...
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13 views

Selecting SVM parameters if training data is oversampled/undersampled

I am working on classification for highly imbalanced data. Let's say I have a strategy to oversample/undersample the training data. I plan to use an SVM classifier to perform the classification. Now, ...
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17 views

Training error higher than test error and validation error

I am training a genetic algorithm for classification and strangely, the training error is consistently HIGHER than the validation and test error. The training and validation set are both small size ...
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1answer
54 views

Scaling data with different importance

I have 9 attributes: x1,x2,x3,x4,...,x9 and I know that the attributes x9 must have the same value in a cluster and the attribute X1 have more importance than others (x2,...,x8) I'm using Euclidean ...
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0answers
13 views

Encoding quantitative outputs for regression

From Elements of Statistical Learning: For a two-class G, one approach is to denote the binary coded target as Y , and then treat it as a quantitative output. The predictions Yˆ will typically ...
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2answers
32 views

How effective is SVM over big datasets?

I have a dataset of 800,000 observations and 11 features that I am using for a classification problem. I tried to optimize my model many times but in vain. The one thing I haven't tried is using SVM. ...
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0answers
17 views

is backpropagation appropriate for training actor-critic when using Neural networks? [on hold]

I'm confused whether the backpropagation is appropriate to train the actor as well as the critic. If it possible I would like to know what is the update part for both. I used already to rain the ...
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1answer
20 views

When does OLS Regression outperform regression tree in term of out of sample prediction?

In my Master thesis i compare ols regression to regression tree to predict wages. I thought that i will get better prediction with the regression tree because it cathes more interactions. But now i ...
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0answers
15 views

Is it useful to add a proportion hyperparameter in the concatenation layer?

I'm reading a paper on deep learning-based recommender systems: Neural Collaborative Filtering. There are two sub-networks, GMF and MLP, which are fused into a unified model, by a concatenation layer. ...
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0answers
23 views

what is a vector perpendicular to a plane of vectors

I have 3 or 4 vectors connected that forms a plane. How can I find the vector that is perpendicular to this plane? it can be a unit vector as long as it preserves this direction. each vector is on ...
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0answers
29 views

How to derive a ranking function by analysing feature correlations

I am analysing some employee details to find the efficiency of the employees. Ideally I want some rankings to rank them based on these features. My features include; current salary projects ...
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2answers
34 views

Define attribute importance in unsupervised learning [on hold]

I'm using 'NbClust' package to help me to get the "optimal number of clusters" and I noticed in my dataset I have attributes with different importance. I have 5 attributes: x1,x2,x3,x4,x5 and I know ...
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7 views

Can Conditional Random Fields(CRFs) become a discriminative model by changing partition function?

In Introduction to conditional random fields, page 24, equation (2.18) and (2.19), the linear-chain CRFs is defined as: $$p(y|x) = \frac{1}{Z(x)}\prod_{t=1}^{T}exp\{\sum_{k=1}^{K}\theta_kf_k(y_t,y_{t-...
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1answer
15 views

About discriminative/generative and directed/undirected graphical model?

I feel that most generative models happen to be DGM(directed graphical model), and most discriminative models are UGM(undirected graphical model). Is there any correlation between these concepts? ...
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20 views

Is there a branch of machine learning that can deal with near infinite state spaces

So I have a game type problem defined as follows; Up to 10 players Each player has: 64 tiles 200 piece types Up to 20 pieces in play at any time There's a random ...
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0answers
4 views

Determining an appropriate cost function given the type of problem and a hypothesis function

I'm studying up on machine learning basics and the standard high-level approach in supervised ML is to define a hypothesis function that maps inputs to outputs. Then define a "cost function" that ...
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0answers
7 views

prepare program code to dataframe for machine learning task [on hold]

I am not sure, that i ask question in the right forum. If necessary, please suggest in which SO forum, I should write this question. I have free source with free program code of different categories (...
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1answer
7 views

Array of samples from multivariate gaussian distribution Python

I am trying to build in Python the scatter plot in part 2 of Elements of Statistical Learning. First it is said to generate 10 means mk from a bivariate Gaussian distribution N((1,0)T,I) and ...
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1answer
32 views

Top principal components versus most significant random forest variables

I was working on making a supervised learning model starting with a database of about 100 features and 1000 data entries. My goal is to predict a certain target variable. I tried three different ...
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0answers
5 views

Implementation of Traditional Language Models

Problem I am now reading this paper (A Bit of Progress in Language Modeling) to know language modeling techniques prior to methods based on neural network. However, since this paper is rather old (...
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1answer
13 views

Suggestion on Papers to Read on Classifier Selection

I'm looking for some papers to read to get started understanding classifier selection method in a computer security system. I wanted to develop a Multiple Classifier System based on a pool of ...
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1answer
18 views

Why Converting Regression to Ordinal Regression

Intro: Ordinal Regression/Classification is a classification where the labels have orders (https://en.wikipedia.org/wiki/Ordinal_regression) Question: Can you comment what are pros and cons if ...
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2answers
39 views

How to find out if there is any real pattern in the data set?

Let's assume that we have a regression problem (in the machine learning sense). Our data set consists of pairs of features vectors and numeric targets. It might be the case that there is absolutely ...
1
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1answer
43 views

Regression on Auction Prices, Multiple Prices Randomness

I'm currently building a model to predict internet auction sale prices of products in a marketplace. There are a lot of instances where a product goes for multiple prices but it's basically the same ...
1
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1answer
21 views

Should I use 5KFold or 10 KFold CV for data about 300000 sample?

I use logistics regression for binary classification. and my data is about 300 000 samples. I have used both kfold = 5 and kfold =10 cross-validation ...
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0answers
13 views

Hypothesis testing on two disproportionate samples

I want to conduct hypothesis testing on conversion rate of two disproportionate samples. One contains 20k Data points and other contains 180k datapoints. How can I do a hypothesis testing on such ...
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1answer
12 views

Model to Recommend Ideal Parameter Changes for Best Performance of Industrial Machine

I'm trying to develop a machine learning model to solve this problem, and am unsure of where to start. We begin with some user-defined settings. The settings are used by a machine to create a product....
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1answer
24 views

Regression when target has a wide range

I'm working on a regression model where I have to predict time. These times go from a few seconds to up to 30 min and more. I calculated the sMAPE through 1 minute bins of the target, and noticed ...