Questions tagged [machine-learning]

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

2,189 questions with no upvoted or accepted answers
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11
votes
3answers
564 views

XGBoost outputs tend towards the extremes

I am currently using XGBoost for risk prediction, it seems to be doing a good job in the binary classification department but the probability outputs are way off, i.e., changing the value of a feature ...
9
votes
1answer
4k views

Catboost Categorical Features Handling Options (CTR settings)?

I am working with a dataset with large number of categorical features (>80%) predicting a continuous target variable (i.e. Regression). I have been reading quite a bit about ways to handle categorical ...
8
votes
0answers
577 views

What is the difference between fasttext and DANs in document classification?

I came across two interesting papers that describe promising approaches for document classification using word embedding. 1. The fasttext algorithm Described in the paper Bag of Tricks for ...
7
votes
1answer
145 views

Improve NER label results on Non-English text

I am working on some Medieval Latin text and was using various methods of NER such as CLTK (Latin Model), Spacy (Multilingual, Italian, Spanish Model) and StanfordNER (Spanish Model). When I used the ...
7
votes
5answers
407 views

What are some of the best practices for sharing data and models with colleagues?

As a data scientist who recently joined a new team, I wanted to ask the community how they share data and models among their colleagues. Currently I have to resort to storing data in some central ...
7
votes
0answers
122 views

Is Minimax Linkage a Lance-Williams hierarchical clustering?

I found the following article on "Hierarchical Clustering With Prototypes via Minimax Linkage". It is stated in Property 6 that Minimax linkage cannot be written using Lance–Williams updates. A ...
6
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0answers
226 views

Finding linear transformation under which distance matrices are similar

I have n sets of vectors, where each set S_i contains k vectors in ...
6
votes
1answer
630 views

Input for LSTM for financial time series directional prediction

I'm working on using an LSTM to predict the direction of the market for the next day. My question concerns the input for the LSTM. My data is a financial time series $x_1 \ldots x_t$ where each $x_i$...
6
votes
1answer
125 views

How to model segmentation of a sequence to similar parts?

I guess LSTM is good for sequence modeling but how would you model "clustering" with it? Meaning, the input is a sequence and the output is labels with similar properties (I have labeled data). For ...
5
votes
0answers
54 views
+50

Time-series prediction: Model & data assumptions in AI/ML models vs conventional models

I was wondering if there was a good paper out there that informs about model and data assumptions in AI/ML approaches. For example, if you look at Time Series Modelling (Estimation or Prediction) ...
5
votes
1answer
157 views

How to compute document similarities in case of source codes?

I try to detect the probability of common authorship (person, company) of different kind of source code texts (webpages, program codes). My first idea is to apply the usual NLP tools like any token ...
5
votes
1answer
113 views

Dealing with population instability

I am working on using machine learning to correctly predict a binary classification using an input dataset that I receive about once a month. The idea is that I train, test and validate the ...
5
votes
0answers
948 views

AdaBoost implementation and tuning for high dimensional feature space in R

I am trying to implement the AdaBoost.M1 algorithm (trees as base-learners) to a data set with a large feature space (~ 20.000 features) and ~ 100 samples in R. ...
5
votes
1answer
1k views

Netflow anomaly detection python packages

Is anyone aware of any open source / python packages for Netflow Anomaly detection ? I found some on github but anyone who has more experience with it. please advise.
5
votes
0answers
435 views

differences between LSQR and FTRL when working with very sparse data

I have a 2M instances dataset with millions of very very sparse dummy variables created using the hashing trick = ...
5
votes
1answer
42 views

Completing MDS manually in R

Given a matrix A, I want to complete Multidimensional Scaling by hand, instead of using any given R functions. As such, I have calculated the centered matrix ...
5
votes
2answers
73 views

Error on multitask neural nets where all outputs not observed for every example

Let's say I have 2 datasets, each from a set of experiments. Dataset A measures a set of properties X for set S, while dataset B measures properties Y for set T. X and Y are highly correlated, and S ...
4
votes
2answers
34 views

How to model a binary classification problem in a evolving environment

Suppose you have a problem with two classes YES or NO. While the YES class is fixed, in the sense that the observations do not evolve, the observations of class NO may evolve during time and may ...
4
votes
2answers
83 views

Is there a rule of thumb when designing neural network in deep reinforcement learning?

In deep learning, we can assess model's performance with loss function value and improve model's performance with K-fold cross-validation and so on. But how can we design and tune neural network used ...
4
votes
0answers
44 views

Training value neural network AlphaGo style

I have been trying to replicate the results obtained by AlphaGo following their supervise learning protocol. The papers specify that they use a network that has two heads: a value head that predicts ...
4
votes
1answer
313 views

Find matching text from a text column

This is my first time to use Data Analytics tool to figure out a solution to a problem. I have a table with following columns ...
4
votes
2answers
266 views

Image recognition of selfie images

I developed an Android app that lets anyone upload pictures of encyclopedic things (bridges, museums, dishes, landscapes, paintings, etc) to Wikimedia Commons. Unfortunately, 5% of the users find it ...
4
votes
1answer
130 views

Training stateful LSTM with different number of sequences

I'm using a stateful LSTM for stock market analysis, and I have varying amounts of data for each stock, ranging from 20 years to just a few weeks (i.e. for newly listed stocks). I use 3 years of data ...
4
votes
0answers
56 views

Predicting change of shapes/coordinates

I'm trying to find a way to predict/calculate how a shape (e.g. outline of a glacier) will change in the future—based on its history (previous shape) and additional factors (e.g. Δtemperature). In my ...
4
votes
2answers
58 views

Classifier that optimizes performance on only a subset of the data?

I'm working on machine learning problem where I'm only interested in getting high accuracy within a narrow band of my predicted likelihoods. Specifically, I want an algorithm that will score very ...
4
votes
0answers
307 views

Hyperparameter tuning in multiclass classification problem: which scoring metric?

I'm working with an imbalanced multi-class dataset. I try to tune the parameters of a DecisionTreeClassifier, ...
4
votes
1answer
362 views

How to deal with position bias in search?

In search, position of the search result affects the click-through rate a great deal. How do people usually deal with this ? In practice how to remove such bias to create unbiased training data for ...
4
votes
2answers
10k views

Multivariate Time-Series Clustering

I have a streaming data along with timestamp dataset that looks like this: 1.png Timestamp can be inclusive of "seconds" too, but the data may or may not change every second. it depends on the ...
4
votes
0answers
308 views

Clustering for high dimensional data

I am have a data set with 52 variables. Most of them have zeros, it resembles a sparse matrix. How can I cluster this kind of data and are there any special types of clustering? I am attaching pca ...
4
votes
0answers
610 views

AUC computation on multilabel classification

I'm using Tensorflow for an auto-tagging task on audio clips. The problem is actually a multilabel classification problem meaning that each clip can have multiple tags at the same time. Regarding ...
4
votes
1answer
543 views

Checkers playing Neural Network evolved with Genetic Algorithm becomes too sensitive to input data changes

I recently embarked on a very ambitious project and I have to say it has turned out a lot better than I expected, I succeeded in coding from scratch a neural network that plays checkers at a very ...
4
votes
1answer
1k views

Convolutional Network for Text Classification

I am trying to train a convolutional neural network with Keras at recognizing tags for Stack Exchange questions about cooking. The i-th question element of my data-set is like this: ...
4
votes
1answer
572 views

Time Series pattern recognition and classification problem

I have some labeled sensor data. Now, I would like to know how to extract features from time series using DFT, DWT, and HAAR transforms. I know that the transformations above transform a signal to ...
4
votes
1answer
392 views

How to implement patternet in python as it is in matlab?

NOTE: This question was first posted in cross-validated website but I was instructed to move it off that website as it was not a good fit. I am new in implementation of machine learning, neural ...
4
votes
0answers
97 views

which loss function (if any) optimizes the calibration graph

The calibration graph is the predicted versus actual probability(see http://scikit-learn.org/stable/modules/generated/sklearn.calibration.calibration_curve.html). Is it possible to optimize the ...
4
votes
0answers
247 views

how to propagate error from convolutional layer to previous layer?

I've been trying to implement a simple convolutional neural network. But I've been stuck at this problem for over a week. To be specific, assume there are 3 layers in a convolutional pass, marked as ...
4
votes
2answers
587 views

AWS machine learning prediction schema problems

I've trained an AWS Machine Learning model with the training data from here : https://www.kaggle.com/c/titanic/data I'm now trying to run a batch prediction with the test data from the same source ...
4
votes
1answer
406 views

Using the Datumbox Machine Learning Framework for website classification - guidelines?

A short while ago, I came across this ML framework that has implemented several different algorithms ready for use. The site also provides a handy API that you can access with an API key. I have need ...
4
votes
1answer
124 views

How to automatically verify official documents?

I am new to machine learning and data science. I apologise if the question seems very basic. I have a requirement where I need to verify information submitted via a form with the corresponding ...
3
votes
0answers
28 views

How do I interpret loss in a neural network?

I am studying how to evaluate the performances of a convolutional neural network, and in particular I have seen that we have to look both at accuracy and loss. I don't understand why do we have to ...
3
votes
1answer
52 views

The output of Model from Decision Tree and Random Forests are different?

I have been made a model using both Decision Tree and Random Forest. But, when I tried to test the model on the same DataFrame the output is different. How is this possible? The data file from my ...
3
votes
0answers
29 views

Features selection with a lot of dummy variables in R

I am performing features selection on 3849 dummy variable (one-hot encoding) using Boruta algorithm and the algorithm is taking forever to run. Is there a faster way I can perform features selection ...
3
votes
0answers
100 views

Learning curve using micro F-score and macro F-score

I plotted the learning curves using micro and macro F-scores for a Multinomial Naive Bayes classifier. The first plot is made using micro F-score, and the second using macro F-score. I find it quite ...
3
votes
0answers
21 views

Heavy regression loss for false non 0 prediction

My regression should predict values >=0 But a wrongly predicted value >0(e.g. 0.001 instead of 0) is much worse then a a slight missprediction of 0.001 (e.g. 0.002 instead of 0.003) I am thinking ...
3
votes
4answers
107 views

Backpropagation: Relevance of the error signal of a neuron

During my quest to understand back propagation in a more rigorous approach I have come across with the definition of error signal of a neuron which is defined as follows for the $j^{\text{th}}$ neuron ...
3
votes
1answer
112 views

Fast Python implementation of the gradient descent

I'm looking for fast Python implémentations of gradient descent optimization algorithm. I have a convex problem , with no constraint, so for now I'm using the BFGS algorithm implemented in scikit-...
3
votes
1answer
108 views

Why is training and validation loss steadily rising (eventually to NaN) in this CNN of mine?

Dear ML and data scientists: I have 4 layers of gray scale images for every single biological specimen in my dataset. I am trying to train a 4-convolution CNN (see pytorch architecture below) to ...
3
votes
1answer
53 views

Evaluating machine learning explainers?

I'm working on a project where multiple machine learning explainers (LIME and SHAP, potentially more coming) are applied to pre-trained models (neural networks) to help explain the predictions of ...
3
votes
2answers
25 views

Pre-trained models

I am starting off with machine learning so could someone tell if there is some site where one can find the current best performing trained models for any specific problem like sentiment analysis or ...
3
votes
0answers
29 views

Why don't Target/LeaveOneOut Encoders work well for Regression Tasks?

In this review of categorical encoding, it states early on that For regression tasks, Target and LeaveOneOut probably won’t work well and later repeats that Target/LeaveOneOut (Owen Zhang's ...