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Kernel ridge regression (KRR), accuracy scale?

What does a good range for the accuracy score look like for the KRR model? For example, RMSE produces a value between 0 and 1, where values closer to 0 represent better fitting models. What's the ...
  • 101
0 votes
1 answer
11 views

Adding another 'hue' to a pairplot

I have plotted a pairplot in Seaborn with a hue, similar to the one shown below. I would like to add another hue by changing the shape of the markers based on another categorical feature. E.g., the ...
  • 1
0 votes
1 answer
5 views

Extract the embedding from a specific layer of MarianModel

I am using using MarianModel from the hub of HuggingFace for a translation task. Now I want to extract the embedding from the output of the last MarianEncoderLayer ...
0 votes
0 answers
4 views

How to calculate total observation time per focal individual across entire observation period?

I have a large amount of data for a set focal individuals that were under observation on a daily basis over three years. I am trying to calculate total times visible doing an activity and not oos (out ...
0 votes
1 answer
12 views

Transform dataset to regression problem by sorting?

I have a raw unlabeled dataset, and I want to design a model to perform a regression. In my dataset, it does not make sense to give each observation a value, but it does make sense to sort them. Can I ...
0 votes
0 answers
3 views

using xmgrace in batch mode

I am using xmgrace to plot 2D bar plot from the following input data: ...
1 vote
0 answers
10 views

Combine datasets of different domains to ehance generalizibility

so I try to implement an Emotion Classifier, which should detect several emotions from a text. There are several datasets for this (ISear, GoEmotions, etc.). However, a lot of them come from different ...
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0 votes
0 answers
6 views

Nearest Neighbor Recommendation System w/ categorical variables

I would like to build a recommendation system: no ratings are available at the time of recommendation, therefore only a purely context-based recommendation system is needed as input features answers ...
0 votes
0 answers
3 views

Likert Scale Target Variable

I have a case study where the target variable (a single factor) gauged through multiple items. the items are measured using 5-Likert scale (Never, Seldom, Sometimes, Often, Very often, Always) since ...
0 votes
0 answers
5 views

clustering customer base purchase behavior

I have a set of data and I want to know that whether they are necessary to add in the clustering analysis. Like ONEOFF_PURCHASES_FREQUENCY, I am not sure it is wether helpful in doing cluster analysis....
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0 answers
12 views

Why am I seeing these spikes in model loss curve

I am training an image classifier on 1152 images in 4 classes , I have used data augmentation too . ...
0 votes
1 answer
13 views

Feature scaling in Linear Regression

I always use Linearregression() class in sklearn library for creating a linear regression model. According to my understanding, we need feature scaling in linear ...
  • 21
0 votes
0 answers
17 views

How can create deliberately biased models?

I deal with an image classification problem with 3-class. I want to create a model which takes side to one specific class. I mean, while the model predicts a sample, if it is hesitant between class-1 ...
  • 101
2 votes
1 answer
102 views

How to train deep learning model on high dimensional dataset with limited memory and disk

For large datasets in terms of rows, usually it is handled by splitting data into pieces and feeding them into the model one at a time using tf.datasets or custom generator. However what if number of ...
  • 375
0 votes
0 answers
11 views

pix2pix TensorFlow Tutorials

I am trying to follow this tutorial, but I want to use my own dataset. The problem I am having is that in this tutorial they merge the realimage and the label image together in to one image( which ...
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0 answers
10 views

is it possible to turn a list of sentences into paragraph?

I have a problem and seeks advise, I have a couple of sentences like: ...
  • 1
0 votes
0 answers
5 views

What is the space and runtime complexity of sklearn MiniBatchNMF

I am trying to scale my virtual machine instance to be the necessary size but not waste extra space. What is the space and runtime complexity for sklearn MiniBatchNMF?
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2 votes
0 answers
15 views

Why is it an advantage "that Markov chains are never needed" to obtain gradients?

In the original GAN (Generative Adversarial Network) paper, Generative adversarial networks by I. Goodfellow, J. Pouget-Abadie, M. Mirza et. al. they state an advantage of the GAN is "that Markov ...
  • 21
0 votes
0 answers
16 views

Border values at which timeseries decrease and increase

I have a timeseries data of signals in stock market ([-1, 1]) and I want to find mean values at which I have down trend and upwards trend. I already used Moving ...
  • 31
0 votes
1 answer
21 views

How do I know that my weights optimizer have found the best weights?

I am new to deep learning and my understanding of how optimizers work might be slightly off. Also, sorry for a third-grader quality of images. For example if we have simple task our loss to weight ...
  • 3
1 vote
1 answer
22 views

How do you train an ML algorithm to achieve a desirable clustering?

Most clustering examples on the net are unsupervised learning. There is a given vectorization into a 2D space and the algorithm discovers clusters. However, what if the input data that I want it to ...
  • 117
0 votes
1 answer
16 views

Testing the impact of events on time series

Context I am working with product data for a retail company. I have the daily impressions (number of times it was viewed online) for all products over a 30 day period (can get more data). Here is the ...
0 votes
0 answers
27 views

What is the best practice for combining cross-validation with hyperparameter tuning and comparing preprocessing methods

The Goal Compare several preprocessing methods and models - while tuning hyperparameters for each model - without leaking information into the final generalization estimate, applying cross-validation (...
0 votes
1 answer
41 views

Binary classification performance difference between 0 and 1 class

I have trained a binary Random Forest classifier on a dataset containing 7M rows. I also set aside a holdout validation set of 1M rows that the training pipeline never sees. The dataset consists of ...
0 votes
0 answers
9 views

Embeded Google Maps map has delay on Oracle Analytics Cloud

I've been using Oracle Analytics Cloud for a while and wondered how to embed the Google Maps map (Dynamic Javascript Map) instead of using the default map. I finally made it work (using an API key ...
1 vote
1 answer
14 views

Newbie questions: real-time clustering of messages

I'm very much a newbie in NLP, so please accept my apologies if this is an obvious question, the wrong place to ask it or any other error I could be making. I am considering using NLP for some subset ...
  • 111
0 votes
0 answers
6 views

IBM SPSS : Different format of CSV file when opened with Notepad and SPSS

I got the data from: https://www.kaggle.com/datasets/rsrishav/youtube-trending-video-dataset I want to use it for college purposes using IBM SPSS Statistics, but when I want to import it to SPSS, the ...
1 vote
1 answer
18 views

Should I annotate additional information besides the categories I already need in a text?

I have a dataset with bank transfer reasons. They vary a lot because humans wrote them. From the reasons that are linked to invoice payments I need to extract several things: invoice number(s) IBAN ...
  • 155
0 votes
0 answers
7 views

loss of exponentially weighted forecaster

In Theorem 2.2 of the book "Prediction, Learning, Games" on page 16 they define the quantity $W_t = \sum_{i=1}^N w_{i,t} = \sum_{i=1}^N e^{-\eta L_{i,t}}$. However, $w_{i,t}$ is defind on ...
  • 109
2 votes
1 answer
36 views

Dummy Variable trap in Linear Regression

The dummy variable trap is a common problem with linear regression when dealing with categorical variables, since one hot encoding introduces redundancy, so if we have m categories in our categorical ...
  • 21
0 votes
0 answers
36 views

Adaptive stopping algorithm find bound that holds with probability

The technique sets aside a validation set Sval, which is used to monitor the improvement of the training process. Let $h_1,h_2,h_3,...$ be a sequence of models obtained after $1,2,3,...$ epochs of ...
  • 101
-1 votes
0 answers
8 views

Which of these dimension reduction algorithm is best for my data

I find many algorithms are used for dimensionality reduction. The more commonly used ones (e.g. on this page ) are: ...
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-1 votes
0 answers
9 views

More dense layers with heavy dropouts or fewer layers with light dropouts?

I'm trying to build a network. While creating the fully connected part in the last, Which one should we prefer: More layers that regularly reduce with heavy dropouts or fewer layers that reduce ...
-1 votes
0 answers
23 views

Difference between Classification and Feature extraction as mathematical problems

I try to understand what is the difference between Classification and Feature extraction as mathematical problems. How i think it works: Assume that we have K scenarios. In classification we try to ...
  • 1
1 vote
0 answers
14 views

LSTM Forecast timeseries with Hyperparameter Tuner (Random Search) from Keras

I want to predict a timeseries with a LSTM Model. I try to use the Tuner from Keras to find the best hyperparameters. data_example: date value 2022-01-02 600 2022-01-03 640 2022-01-04 605 ... ... ...
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0 votes
1 answer
16 views

Difference between Siamese Network and Prototypical Networks for One Shot Learning

I am having a bit of trouble understanding how the architecture of prototypical networks in a one shot learning use case differs from Siamese networks. If I’m understanding correctly, Siamese networks ...
0 votes
0 answers
7 views

Confusion on DCGAN generator project & reshape

I've been recently studying DCGAN. I tried following implementation from the pytorch.org DCGAN tutorial and found that it (seemingly) lacks project & reshape layer, which is present in the diagram:...
-1 votes
0 answers
13 views

Which classification model to select

I have a classification problem where I need to identify whether a transaction will fail or succeed. The dataset is about 50,000 records. As per my understanding, using Naive Bayes classified, ...
  • 1
-1 votes
0 answers
17 views

Graph Execution Error when dealing with ordinal encoded data

While running a neural network where one of the features was encoded using ordinal encoding, the unknown values in the test data was handled by filling in as -1 using the unknown_value parameter. ...
  • 1
1 vote
0 answers
20 views

Incorporating error values (uncertainties) into DBSCAN

Suppose I have a set of coordinates (x,y,z), corresponding to ~800 points. I am currently using DBSCAN with a custom metric function (taking angles as an input, ...
-1 votes
1 answer
14 views

How do the intercept and slope calculated in linear regression relate to the output of lm?

I have been looking at how to calculate coefficients by hand and the example produces $Y = 1,383.471380 + 10.62219546 * X$ However the output shown of lm does not show these values anywhere. How do I ...
  • 101
2 votes
1 answer
68 views

Predict actual result after model trained with MinMaxScaler LinearRegression

I was doing the modeling on the House Pricing dataset. My target is to get the mse result and predict with the input variable I have done the modeling, I'm doing the modeling with scaling the data ...
0 votes
0 answers
13 views

How do I answer this metric question with the data I have?

I want to see what is contributing to the increase in appointments being made by patients. I have two datasets I'm analyzing and I'm not sure if I can use one column to compare with another column. ...
  • 1
0 votes
0 answers
15 views

Sklearn SVM slower than when run in GridSearchCV

Problem: Running SVM in GridSearchCV is faster than running without it and supplying only 1 value of C and no CV. The AUC on the test set is lower when SVM is run outside of GridSearchCV. Background:...
0 votes
2 answers
23 views

Finding observations that are most similar in some regards but most different in others

I have a data set of about ~75 administrative regions. Among many other variables are four specific demographic variables, and a number which represents per-person funding from a government grant. I ...
  • 1
0 votes
1 answer
9 views

Filter out transactions occurring within a timeframe with the same amount

I need to apply some filtering on a data frame using pandas. Basically my data frame has the following column: ID - The row id of the transaction Timestamp - object was transformed to datetime format ...
  • 1
1 vote
1 answer
13 views

adding conditional variables

I am working with NBA df. I have columns with total stats for each player. Stats(columns), total careeer only, are: games played, points, rebounds... There's 17 of them. Here's what it looks like for ...
0 votes
1 answer
25 views

Increasing/Decreasing importance of feature/thing in ML/DL

I have 3 cases: I have a classification model that will be used to classify cats and dogs. On my train data dog pictures has a watermark on them, but cat pictures don't. The problem is: Whenever I ...
  • 89
0 votes
0 answers
17 views

Which algorithm to use for predictors which are sparse for classification problem

I have a classification problem with target has 85% to 15 % ratio (0,1) and around 35 predictor which all are 0 or 1 , I tried building logistic regression however the auc is around 0.53 , I am not ...
0 votes
0 answers
9 views

Why does Vertex AI's Confusion Matrix data decreases as I increase confidence threshold?

This is a binary classification AI. To me, it does not make sense for the total data in the Matrix to decrease. After all, the system only has 4 options (True Positive, True Negative, False Positive, ...

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