Questions tagged [machine-learning]

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

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350 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 $\mathbb{R}^d$. I know there is some unknown linear transformation $W$ under which the distance matrix $D_i$ (a $k\times k$ ...
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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 ...
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2answers
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Which classification algorithms are negatively affected by class imbalances?

I've seen a few posts and papers floating around the web (mostly those related to over/undersampling, SMOTE, and cost-sensitive training) that, when discussing class imbalance, specify that certain ...
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1answer
732 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 $x_i$...
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1answer
581 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 ...
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2answers
87 views

Predict a sequence given many sequences

I'm trying to find an algorithm that would fit this use case: My data: a bunch of fixed-size integer arrays, e.g. [0,2,3,4,5] [1,2,3,1,5] [4,1,2,4,5] ... Input: ...
5
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1answer
107 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 ...
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0answers
85 views

Robustness of ML Model in question

While trying to emulate a ML model similar to the one described in this paper, I seemed to eventually get good clustering results on some sample data after a bit of tweaking. By "good" results, I mean ...
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2answers
1k views

Combining Machine Learning classifier with NLTK Vader for Sentiment Analysis

As a part of my university project, I am researching/developing a sentiment analysis model wherein I am trying to combine NLTK Vader (SentimentIntensityAnalyzer) results with a Machine Learning ...
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1k 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
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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
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1answer
129 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 ...
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459 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 = ...
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2answers
52 views

Robustness of hyperparameter tuning

I use a Bayesian hyperparameter (HP) optimization approach (BOHB) to tune a deep learning model. However, the resulting model is not robust when repeatedly applied to the same data. I know, I could ...
4
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1answer
46 views

Training Machine Learning Model - Neural Network - Islands Problem

I was working on the following leetcode problem: Given a 2d grid map of '1's (land) and '0's (water), count the number of islands. An island is surrounded by water and is formed by connecting ...
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1answer
165 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 ...
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2answers
42 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
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2answers
2k views

GAN - am I seeing mode collapse? Common fixes not working

I have a 2 part question. Context I am learning about GANs and writing my own starting from the very simplest example of adversarial learning (1-parameter node), then implementing a very simple 1-...
4
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1answer
513 views

K Nearest Neighbour with different distance matrix to each datapoint

I'm wondering if there is library support in python (such as sklearn) for doing KNN on a data set that has a custom distance matrix (positive definite) for each data point (x is a query point, $x_i$ ...
4
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2answers
922 views

Training NLP with multiple text input features

Question: How can I train a NLP model with discrete labels that is based on multiple text input features? Background: I'm trying to predict the difficulty of a 4-option multiple choice exam ...
4
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1answer
419 views

ML regression poor performance

I am experimenting with 3 years time series electrical demand data (kW) for a building and attempting to create regression supervised ML models from sci kit learn regressor algorithms but I have very ...
4
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2answers
93 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
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0answers
325 views

How to handle preprocessing (StandardScaler, LabelEncoder) when using data generator to train?

So, I have a dataset that is too big to load into memory all at once. Therefore I want to use a generator to load batches of data to train on. In this scenario, how do I go about performing scaling ...
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0answers
52 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
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2answers
662 views

How can I use two different datasets as a training model for svm

I know that you're supposed to scale your test data using the parameters (mean and stdev) from your training data. This is relatively simple; but what if the number of samples is limited in one ...
4
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2answers
429 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
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1answer
160 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
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1answer
71 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
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0answers
279 views

Multiple activation functions with TensorFlow estimator DNNClassifier

I just want to know if is it possible to use tf.estimator.DNNClassifier with multiple different activation functions. I mean, could I use a DNNClassifier estimator which use different activation ...
4
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0answers
398 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, ...
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0answers
167 views

Confidence value in AdaBoost?

I read this introduction about AdaBoost (http://www.cs.man.ac.uk/~nikolaon/~nikolaon_files/Introduction_to_AdaBoost.pdf), and am curious why confidence for each model is defined as $$\alpha_j=\frac{...
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0answers
149 views

How to do give input to CNN when doing a text processing?

As a signal processing engineering and being new to NLP, I am confused with giving input to CNN network. With my knowledge of CNN, I am trying to build a classifier for ethnicity with inputs as text ...
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0answers
66 views

make prediction with a time serie

I want to build a model that can detect which driver is driving now the car based on a dataset that contains 20 driver records for 3600s each driver ( the dataset contains all the car sensors values ...
4
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0answers
661 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
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2answers
210 views

Support Vector Regression trained with data sets

I am now searching for a long time on the internet and on papers for an answers of simple questions. Am I able to train a Support Vector Regression algorithm with different data sets? If yes, how is ...
4
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1answer
625 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
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1answer
464 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
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0answers
258 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
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0answers
395 views

Illustrating the dimensionality reduction done by a classification or regression model

Tl;DR: You can predict something, but how do you explain the prediction? Your usual classification/regression setup Lets say the data is a classic regression/classification problem: several ...
4
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1answer
168 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
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1answer
18 views

How to perform data scaling/standardization on dataset containing grouped values?

So I have a dataset containing the results of executing problem instances with different given solver strategies. Simplified example: ...
3
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1answer
39 views

Practical limitations of machine learning

Working on some applied machine learning problems, I've started to encouter some practical difficulties. Those difficulties relate to - but are not limited to - : convergence of the learning process, ...
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0answers
20 views

Possible flaw in the MDS method for dimensionality reduction

The MDS (multidimensional scaling) method is used to solve the problem of dimensionality reduction. Basically, it does the following: given $n$ points $x_1,\cdots,x_n\in\mathbb R^d$, try to find a ...
3
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0answers
120 views

Chess deep learning siamese network overfitting when shouldn't in theory

TLDR: My network is training with pairs so instead of 10^6 samples it has 10^12 samples (The number of samples squared) . With that large of a data set is shouldn't overfit but it does after very few ...
3
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1answer
75 views

Segmentation Network produces noisy output

I've implemented a SegNet and SegNet ReLU variant in PyTorch. I'm using it as a proof-of-concept for now, but what really bothers me is the noise produced by the network. With ADAM I seem to get ...
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0answers
98 views

How to detect vanishing and exploding gradients with Tensorboard?

I have two "sub-questions" 1) How can I detect vanishing or exploding gradients with Tensorboard, given the fact that currently write_grads=True is deprecated in the Tensorboard callback as per "un-...
3
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1answer
91 views

tensorflow pseudo inverse doesn't work for complex matrices!

The Tensorflow documentation here says that: tf.linalg.pinv is ''analogous to numpy.linalg.pinv. It differs only in default value of rcond''. However, tf.linalg.pinv requires the matrix to ...
3
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0answers
450 views

How to apply a groupby rolling function to create multiple columns in the dataframe

I am setting up a volume profile series over a stock data. I have implemented the market profile code from this github repo and the link to the data is here and the example here. Some Sample of data ...
3
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0answers
41 views

How can I improve the accuracy of my model? (Cab Cancellation Prediction)

I am trying to predict based on several parameters like trip type, car type, source of booking, start time, lead time (start- book) and a few other params whether or not a customer will cancel. From ...
3
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1answer
37 views

Data prediction using scikit-learn and a list

I have a group of lists detailing temperatures over differing amounts of time. My goal is to use machine learning to identify periods in which a machine is turned on and off, where turning on the ...

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