Questions tagged [machine-learning]

Machine Learning is a subfield of computer science that draws on elements from algorithmic analysis, computational statistics, mathematics, optimization, etc. It is mainly concerned with the use of data to construct models that have high predictive/forecasting ability. Topics include modeling building, applications, theory, etc.

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21 views

How to get periodicity from timeseries data?

I would like to create a recommendation system for a smart home application. I gather the data in a time-series database. The app monitors the on/off state of a smart lamp and can create daily ...
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27 views

Is it wrong to transform the target variable and test the model without dropping the column that was transformed? What's the disadvantage about it?

I have a linear regression model, I have transformed the target variable Item_Outlet_Sales into Item_Outlet_Sales_log on both training and testing dataset. I did not delete the Item_Outlet_Sales. Here ...
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1answer
22 views

Predicting high frequency sparse time series data in python

I have a dataset of a couple of EV charging stations (10 min frequency) over 1 year. This data consists of lots of 0's, since there is no continuous flow of cars coming to charge but rather ...
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how to quantify contribution of each data point in a deep learning model?

I am trying to understand how much each data point contributes to the training of a deep learning model and wonder if anyone has any idea how to do that. Theoretically, I could remove one data point ...
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1answer
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same or different number of epochs for dataset of different sizes?

I am trying to fit a DL model on a dataset, after a while of parameter tuning, I have determined the optimal number of epochs. Now suppose there are new data available and I would like to include ...
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How can I prevent overfitting?

hope to find you well ! I am trying to build a model to classiffy customers with propensity to buy, but i cannot get rid of overfitting! My approach is the following: I have created the train dataset ...
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1answer
29 views

Are we allowed to transform the continuous target variable by creating a log transformation in order to have a normal distribution?

The following code gives the target variable Item_Outlet_Sales before transformation and Item_Outlet_Sales_log which is transformed ...
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0answers
20 views

Coordinates of cereals in figure

I'm trying to automatize cereal counting from an image. The problem is that I have only a few pictures and I don't know how to train a CNN to do the job. Should I create mini images with single ...
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2answers
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Do larger numbers of hidden layers have a bigger effect on a classification model's accuarcy?

I trained different classification models using Keras with different numbers of hidden layers and the same number of neurons in each layer. What I found was the accuracy of the models decreased as the ...
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16 views

Predicting sparse time series data

I have a dataset of a couple of EV charging stations (10 min frequency) over 1 year. This data consists of lots of 0's, since there is no continuous flow of cars coming to charge but rather ...
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0answers
15 views

How would you optimize this Binary Text Classification model further? The data set is large (40000 texts)

I'm learning about tensorflow/keras since a couple months. What are some methods to reduce overfitting in the later epochs or increase val. accuracy in general? train data dim (40000,70) (reddit ...
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How to resolve IndexError while doing Monte Carlo for 1000 runs? [closed]

Below code runs without any problem, however when I run the same code using Monte Carlo Analysis for 1000 runs, it gives IndexError. Can someone explain why this happens. Thanks ...
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1answer
29 views

best similarity measure for images with different angles

I want to compare different images (where the images are of the same setup but the angles with which the images are taken are different). I want to obtain some sort of similarity score. I tried using ...
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1answer
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Which Policy Gradient Method was used by Google's Deep Mind to teach AI to walk

I just saw this video on Youtube. Which Policy Gradient method was used to train the AI to walk? Was it DDPG or D4PG or what?
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Dealing with null values in categorical string data

Which of the following is a better approach in dealing with null values and why? Fill the null values with the mode (most occurring value). Consider the null itself as a category by converting it to ...
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2answers
28 views

Linear Regression with Category variables

I'm currently learning and exploring machine learning and understand the basics of linear regression based on two numerical variables, but now I wish to go a little further and need some guidance ...
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1answer
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Why is DDPG a Policy Gradient Method? [closed]

Why is DDPG a Policy Gradient Method even though it's actor does not output probability?
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24 views

Having trouble reducing MSE error for SVR model sklearn

I'm trying to create an SVR model to predict the number of comments a headline will receive for the following dataset : https://www.kaggle.com/benjaminawd/new-york-times-articles-comments-2020?select=...
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15 views

ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type int) [migrated]

I am trying to tune the hyperparameters of MLP sequential model but getting an error while performing this task. I have tried degrading/upgrading the scikit-learn version and using ...
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18 views

How metric learning works for content based item retrieval

I was doing some computer vision experiments and recently I have started learning about metric learning and the image retrieval problem. I was experimenting with the inshop image retrieval dataset to ...
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1answer
15 views

Unbalanced training set from balanced data

I am looking to get an unbalanced training set with a given ratio of classA:classB from a dataset without regarding if it is balanced or not. The point is to analyze the influence of data imbalance on ...
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1answer
26 views

Using Linear Regression to Learn Polynomial Regression

Let's start by considering one-dimensional data, i.e., $d=1$. In OLS regression, we would learn the function $$ f(x)=w_{0}+w_{1} x, $$ where $x$ is the data point and $\mathbf{w}=\left(w_{0}, w_{1}\...
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Load data from SQL for Machine Learning

I have an SQL DB which has millions of records(10 years of data) and wanted to implement some ML Models. Most of the courses/tutorials explains using a local file or downloaded CSV. But in my case I ...
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2answers
88 views

Is reinforcement learning a subset of unsupervised learning?

According to this article: Reinforcement learning on the other hand, which is a subset of Unsupervised learning ... How true is this statement? Is there any scholarly discussion/writing on the ...
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8 views

How to realize a 4 dimensional time series data classification

Assuming I am doing a speech binary classification. An audio file contains a different number of sentences. I am splitting the audio files by their sentences with padding to a fixed number of ...
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1answer
16 views

Is it possible to extract specific words from a sentence in Hindi/Marathi?

I have seen the different options to extract words from sentences in English but when I wanted to know if its possible to do the same thing in Hindi or Marathi eg: टोमॅटो बेचना है where the word at ...
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21 views

What should be the architecture design for the dataset to be used for a machine learning API

I have aroud 30GB of market dataset in csv format which is downloaded onto my server computer everyday. Now I want to use this dataset to do some computations and provide some analysis. The user will ...
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14 views

Adding layer to a trained CNN to process higher resolution images. Tried 2 schemes, 1 works fine, 1 fails completely

I'm working with images coming from a sensor, for which 1 pixel corresponds to 2 mm in the real world. I've built and trained a CNN that does semantic segmentation of the image (128x128 pixels) and it ...
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0answers
7 views

How to handle features containing strings in XGBoost in AWS Sagemaker

How can i handle the string containing spaces and colons as a feature for my xgboost classifier model? AWS Sagemaker requires the input in csv format, I don't know how to convert the string to the ...
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1answer
27 views

Logistics Demand Forecasting with 20k Different Time Series

I'm trying to tackle a very challenging problem and I would appreciate your help. My organization has a lot of different items which can be demanded by our clients. Those items can also be returned ...
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0answers
18 views

Suitable CPU with RTX3070 GPU for deep learning [closed]

I am trying to get a GPU for my deep learning research. Due to stock limitation, I can only get a RTX3070. In my lab, there's some PC/workstation whereby I can install the RTX3070. However, I wonder ...
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0answers
57 views

VC-Dimension of Axis Aligned Right-Angle Triangles and 5-points Convex Hull

I am having trouble proving the following fact about VC dimension of triangles. Consider right-angle triangles in the plane, with the the right-angle in the lower left corner. The hypothesis in our ...
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0answers
26 views

Using softmax for multilabel classification (as per Facebook paper)

I came across this paper by some Facebook researchers where they found that using a softmax and CE loss function during training led to improved results over sigmoid + BCE. They do this by changing ...
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0answers
12 views

Imbalanced dataset, finding the statistical significance of a Matthews Correlation Coefficient (MCC) in binary classification (what is a good MCC)?

I have a very imbalanced dataset. Thus, I am using MCC to evaluate the performance of various ML algorithms. It appears that literature is entirely lacking in ways to evaluate how good an MCC score is....
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1answer
22 views

Are there any tree-based models that use a genetic algorithm to generate the trees?

I have a large dataset (195 features x 20m samples) that I have trained using XGBoost. I would like to see if a genetic algorithm can beat XGBoost since the data has so much noise it is prone to ...
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2answers
112 views

How to use a set of pre-defined classifiers in Adaboost?

Suppose there are some classifiers as follows: ...
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1answer
24 views

Calculate implicit rating from streaming behaviour for Recommendation Engine

I have a dataset containing some user streams data for particular videos like below: ...
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1answer
14 views

Difference between bagging and pasting?

I found the definition: ...
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0answers
15 views

Predicting in decision rules

Sequential covering is a type of decision rule procedure that repeatedly learns a single rule to create a decision list (or set) that covers the entire dataset rule by rule. Given a training dataset, ...
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0answers
15 views

Why is my accuracy 0 on the first epoch in continuous training on MNIST

I'm trying an experiment where I first train my model on MNIST labels [0-4], and then I freeze the first conv layers and continue training my model on labels [5-9]. When I dont re-initialize my Fully ...
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2answers
38 views

Determining whether a sentence is “cliche” using NLP

I have a collection of essays from students. Each essay is about the same topic and of the same word length. My goal is to develop a machine learning algorithm that pinpoints "cliche" ...
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1answer
30 views

Notebook for data science

I'm searching for an online Jupiter notebook environment that allows collaborating in real-time. I've found that I've choice from two services Deepnote.com and DataLore by JetBrains. I have little ...
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1answer
29 views

Why my classification accuracy is high for both training and testing data?

I have a dataset with 10 features and 1 binary classification target. I tested this dataset with decision tree classifier. I did some basic check like missing values but the data looks clean. My ...
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0answers
8 views

How to customize a objective funtion in xgboost?

I am new to xgboost and not so good at math. I want to use a self defined objective function, here is the expression: ...
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1answer
65 views

KFold cross validation ambiguity

I just studied K-Fold cross validation technique for finding model parameters and something seemed to be very confusing. Every tutorial I follow says that for K-Fold validation, the whole dataset will ...
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1answer
13 views

when will the incareful features harm the model?

I am working on financial prediction problem(time-series prediction problem). I think feature engineering is importance in this problem. So i am careful to check the feature's effectiveness. And i ...
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1answer
37 views

Why my regression model always be dominanted by one feature?

I am working on a financial predict problem. which means it is a time series prediction problem. I have three features, which have high correlation(each two's corr is about 0.6) And I do the linear ...
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3answers
37 views

Are there ML Libs in Python robust to missing data?

So I was searching on how to handle missing data and came across this post from Machine Learning Mastery. This article states that some algorithms can be made robust to missing data, such as Naive ...
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1answer
17 views

Is it a good idea to combine fine tuning and feature extraction techniques?

I have a normal/tumor medical images dataset and, for the same patients, also the relative genomics, and my goal is to predict if a patient has a tumor by combining all the information. To achieve ...

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