Questions tagged [machine-learning]

Methods and principles of building "computer systems that automatically improve with experience."

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1answer
2k views

Price prediction based on historic data

Im new to ML. I'm trying to predict if a new Music Album will exceed X amount of dollars in Sales. I'm looking to build a model to go only after potential best sellers. I do have historic data for ...
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1answer
1k views

HDBSCAN cluster: still unclear to me how to chose 'min_cluster_size`

Hdbscan is an excellent technique to find the "optimal" number of clusters within your data when you have little a priori idea how many clusters should exist. This makes the method great for ...
3
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1answer
542 views

Gap leaderboard score and model scoring on a Competition

I'm working on a Veolia challenge on Ens Data Challenge ens-data (equivalent to Kaggle) the goal is to classify very rare binary events (the failure of a pipeline ) for 2014 and 2015 (y={2014,2015}). ...
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1answer
102 views

Learning with groups of sequential data

Say I have a data set such as the following: person, Time, Value, Event person1, 2010-07-02 00:00:00, 5.4, 0 person2, 2010-07-02 10:00:00, 12.7, 0 We have a ...
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1answer
984 views

ML algorithm for determining CSV file header names based on content

I have a large amount of CSV files, an example of which (for job titles) is listed below. The data is noisy (there are misspellings, difference in capitalisation, missing values, and they are not well-...
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2answers
383 views

Are there Machine Learning Models for Networks?

I am working on a regression problem, where the goal is to estimate historic traffic volumes throughout a transportation network. I have traffic counters at 100 locations, so a model can learn the ...
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1answer
79 views

Explaining machine learning models [closed]

Is there a way to get an explanation of the model prediction for a specific example?
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2answers
7k views

Learning rate in logistic regression with sklearn

In sklearn, for logistic regression, you can define the penalty, the regularization rate and other variables. Is there a way to set the learning rate?
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2answers
40k views

Could not convert string to float error on KDDCup99 dataset

I am trying to perform a comparison between 5 algorithms against the KDD Cup 99 dataset and the NSL-KDD datasets using Python and I am having an issue when trying to build and evaluate the models ...
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0answers
505 views

HMM - Matlab for data set to detect anomaly

I have a dataset of oil temperatures. The time series consist of 100 hours of measurement at every second. There is an anomaly in the data that I would like to detect using Hidden Markov Models (HMM). ...
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0answers
104 views

Regression for binary classification and AUC metric

In the kaggle forums I found an example model where someone was using XGBRegressor for a binary (0/1) classification problem (sorry, cannot find the link any more). This was for a competition where ...
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1answer
2k views

Named entity recognition (NER) features

I'm new to Named Entity Recognition and I'm having some trouble understanding what/how features are used for this task. Some papers I've read so far mention features used, but don't really explain ...
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2answers
2k views

Is standardization needed before using scikit-learn SVM?

I am using the SVM function provided by scikit-learn. I would like to know whether I need to perform standardization before fitting the model. As I know, LibSVM ...
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4answers
14k views

Interpreting Decision Tree in context of feature importances

I'm trying to understand how to fully understand the decision process of a decision tree classification model built with sklearn. The 2 main aspect I'm looking at are a graphviz representation of the ...
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3answers
2k views

Keras: X and Y are the same, yet validation accuracy is 50%, what is wrong?

I am trying to understand what is going on so I built a simpler version of my project. I set the X and the Y to be identical and I'm trying to predict Y using X, this should be very simple, but my ...
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2answers
8k views

Could Deep Learning be used to crack encryption?

Say you have a dataset with millions of rows and the attributes Plain Text, Key, and Output Ciphertext. Could Deep Learning, theoretically, be used to find patterns in the outputs that help decipher ...
2
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1answer
226 views

What is the difference between Slow Feature Analysis (SFA) and a Moving Average?

I have started to read more about Slow Feature Analysis and I was wondering how SFA differed from simply taking a moving average? The linked article suggests, "SFA is an unsupervised algorithm that ...
1
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1answer
242 views

Ad click prediction: what are the negative examples?

I am analysing the log of a website and I would like to build a classifier to predict the users that are likely to click on an Ad. The Ad can be displayed to the visitor several times. To build any ...
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2answers
116 views

Is my general understanding of finding weights correct?

I started a course in Deep Learning. I'm trying to make an example in order to explain to myself how the weights are found mathematically. If what I wrote below is nonsense I'll be glad to hear an ...
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2answers
396 views

Modern Feature Selection Review/Resources

I found this review paper by Guyon and Elisseeff in a 2003 JMLR publication but, although not outdated, it is quite old. Is there a more recent review or resource on the topic of feature selection? ...
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2answers
763 views

Interpret results from a lightFM factorization machines

I built a recommendation model on a user-item transactional dataset where each transaction is represented by 1: model = LightFM(learning_rate=0.05, loss='warp') ...
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2answers
7k views

What is the difference between data-driven methods and machine learning?

I was wondering (about a more semantic question), is there a difference between data-driven methods and machine learning? Or is it more correct to state that machine learning is a category of data-...
0
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1answer
533 views

Modeling pixel intensity with the normal distribution

I was reading a machine learning book with applications in computer vision. In it, it mentioned that "in vision, it is common to ignore the fact that the intensity of a pixel is quantized and model it ...
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3answers
1k views

Machine Learning - Choice of features for determining hypothesis

I am a newbie to machine learning and have the following elementary questions. Given a labeled dataset with multiple features, is it for a ML algorithm determine on its own what features are to be ...
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0answers
739 views

Generalization error for simple linear regression

Lets say we have a training data and we have estimated a fit for a model of square ft of living area vs price of houses. Suppose we know the probability distribution of sq ft and for a fixed sq ft we ...
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1answer
123 views

Understanding portfolio-level risk models

I have a tremendous amount of experience training supervised machine learning models. However, I recently became a data scientist at a small financial services company, and I've been asked to build ...
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1answer
1k views

How to reverse ReLU activation in deconvolution

I recently came across Matt Zeiler's deconvolution (reversing convolution) paper . How is deconvolution able to reverse the rectified scalar output? From what I understand it sounds analogous to ...
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0answers
75 views

Python svm classification, result vs amount of features not as expected

After helpful advice from here, i have started my ML journey with SVM. Initially i started with 15 features and after cross validation i got about 40% accuracy. Problem is when i decided to just load ...
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1answer
565 views

Machine Learning - Range of Hypothesis space and choiceof Hypothesis function type

I am new to machine learning and seek your help in clarifying my elementary doubts. I did a fair amount of googling, but find most literature jumping directly into math. What I know is that given a ...
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2answers
8k views

Text similarity using RNN

Data set contains records of short text, typically a sentence. The goal is to find duplicated records and similar records. Currently, I have tried R package 'text2vec', the glove word vectors and the ...
2
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1answer
513 views

Basic backpropagation question

I'm attempting to create my own neural network optimization model from scratch. I'm getting hung up on backpropagation. I have just a few basic questions: When adjusting a given weight by the ...
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2answers
1k views

Which deep learning framework have support for gtx580 GPU? [closed]

I would like to train convolutional neural networks using a gtx580 gpu. I tried setting up TensorFlow but it did not work (wrong cuda compute compability). Which deep learning framework can best ...
3
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1answer
1k views

Are there established good algorithms for incremental feature learning for a neural network? Do any python ML libraries implement such algorithms?

I'm working with a high-dimensional dataset, and have found that my attempts at dimensionality-reduction hurt the accuracy of downstream classifiers, suggesting that I am effectively losing ...
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4answers
4k views

Machine Learning vs Deep Learning

I am a bit confused by the difference between the terms "Machine Learning" and "Deep Learning". I have Googled it and read many articles, but it is still not very clear to me. A known definition of ...
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2answers
782 views

Why the number of neurons or convolutions chosen equal powers of two?

In the overwhelming number of works devoted to the neural networks, the authors suggest arhitechure in which each layer is a numbers of neurons is power of 2 what are the theoretical reasons(...
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3answers
73 views

Feature usage for machine learning algorithm

Given a list of software installed by users as features, e.g., Microsoft_VC80_DebugCRT_x86_x64 1.0.0; Microsoft_VC80_DebugCRT_x86 1.0.0; ;Windows UPnP Browser 0.1.01;Adobe Acrobat Professional 10; I ...
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2answers
213 views

How to present the final model (e.g. random forest)?

I've run random forest on my dataset (imbalanced, binary target class) and used cross validation to tune the parameter and use recursive feature elimination with cross-validation to get the subset of ...
5
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3answers
409 views

Can you recommend a machine learning challenge that is suitable for novices?

I am looking for a challenge that is suitable for a group of novices who want to learn the basics of data science and machine learning. The challenge should match the following criteria: is based on ...
1
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1answer
168 views

Association Rule Learning for Home Electricity or Water Data?

My university has a building on campus where electrical usage and water usage is monitored down to the second. Many electrical loads and water usageis tracked and stored in a database. In the water ...
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2answers
487 views

How to improve accuracy further for forest cover prediction

I am doing Forest-Cover-Type-prediction on Kaggle this is the train and test data > dim(train) [1] 15120 56 > dim(test) [1] 565892 56 So far I ...
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4answers
12k views

Pattern Recognition on Financial Market

Which machine learning or deep learning model(has to be supervised learning) will be best suited for recognizing patterns in financial markets ? What I mean by pattern recognition in financial market ...
1
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1answer
321 views

Digits Localization on Streets View House Numbersm

I am trying to learn a bit of deep learning playing with the Street View House Numbers data set. I have managed to recognize sequences of digits and I'd like now to train a CNN to localize digits and ...
2
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1answer
460 views

Classification problem approach with Python

I am a Python beginner, just getting into machine learning and need advice on the approach i should use for my problem. Here is an example of my data-set. Where the RESULT is a corresponding INDEX ...
3
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2answers
837 views

My ADALINE model using Gradient Descent is increasing error on each iteration

I have used the Iris Dataset's 1st and 3rd Column for the features. and the labels of Iris Setosa (-1) and Iris Versicolor (1). I am using ADALINE as a simple classification model for my dataset. I am ...
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1answer
2k views

Recognize Street View House Numbers

I am new to deep learning and I am trying to train a NN to recognize house numbers gathered from street view. I have already managed to recognized MNIST sequence of hand written digits by means of a ...
4
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2answers
1k views

Neural Network accuracy and loss guarantees?

This question is part of a sample exam that I'm working on to prepare for the real one. I've been stuck on this one for quite a while and can't really motivate my answers since it keeps referring to ...
4
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2answers
1k views

Normal equation result simplification

The derivation of the normal equation can be noted $\theta = (X^TX)^{-1}(X^T)y$, where $X^{-1}$ is the inverse of $X$ and can also be written $inv(X)$. But why can't we write $inv(X^T X)$ as $inv(X)...
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0answers
365 views

Mapping xml tags by Rule Learning/Generation Algorithms

I'm trying to map tags/attributes from xml files from different sources. I've found a paper called Semantic Mapping of XML Tags using Inductive Machine Learning. Among various things, it also talks ...
1
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1answer
593 views

Difference between subgradient SVM and kernel SVM?

What is the difference between subgradient svm and kernel svm? From my understanding subgradient svm is a linear classifier that uses hinge loss and kernel svm uses some kernel function for non ...
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2answers
4k views

Binary Classification on small dataset < 200 samples

I have a dataset consisting of 181 samples(classes are not balanced there are 41 data points with 1 label and rest 140 are with label 0) and 10 features and one target variable. The 10 features are ...

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