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31 views

TF/keras implement residual block

I read several papers, where they propose to implement residual blocks of ResNet as follows $$ u^{k+1} = u^k - \tau K^T \sigma(K u^k), $$ where $u^{k}$ denotes output on k-th layer, $\tau$ is ...
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1answer
21 views

What exactly is convergence rate referring to in machine learning?

My understanding of the term "Convergence Rate" is as follows: Rate at which maximum/Minimum of a function is reached, so in logistic regression rate at which gradient decent reaches global ...
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1answer
16 views

Calculating confidence score in NER

I am working on a problem on Named Entity Recognition. Given a text, my model is detecting the Named Entities and extracting that info for the end user. Now the ask is end user needs a confidence ...
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0answers
13 views

Recommender System Approaches

I have a 4 datasets with user features, item features, user-item rating and User-item link data. I'm trying to build a recommender system to recommend top 10 items to the user by maximizing NDCG as ...
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0answers
13 views

What model should i use to extract relation between words

I want to create a ML model which would give a score from 0 to 1 which would signify the relation between them. I know about Relationship Extraction(RE) but that's more related with sentences based ...
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0answers
10 views

Predicted probabilities of Multi Label Classification

I'm currently working on a Kaggle Competition wich objective is to predict probabilities of an ID belonging to each class. There are 4 posible classes. The data is tabular and because it's a Kaggle '...
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1answer
18 views

Can someone explain to me how to use a predictive model to predict something other than the training set

So let's say I create a logistic model to predict who will open a loan based on a based email list that includes who opened and who didn't that's 90% accurate. The model says age, income, bank ...
1
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1answer
26 views

Use trained non linear regression model to identify variables that maximize the predicted value

I trained a non-linear regression model with 23 features. I tried to make sure the model doesn't overfit with ~0.6 r squared on validation data and with 0.75 correlation coefficient between the actual ...
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1answer
15 views

Best parameters to try while hyperparameter tuning in Decision Trees

I want to post prune my decision tree as it is overfitting, I can do this using cost complexity pruning by adjusting ccp_alphas parameters however this does not seem very intuitive to me. From my ...
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1answer
10 views

Linear Learning Machines

I was reading about Linear Learning Machines (LLMs) and learned that it is closely related with SVMs. Would like to know an example of any concrete problems that can be classified by LLM as I couldn't ...
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0answers
7 views

How to inform tree based methods about sequence of data

I am using tree-based methods for predictions, my series are such that they are usually high but then they slowly decrease to a lower level, I am giving the month and exogenous things as feature, but ...
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0answers
11 views

Using machine learning to find the most similar image that contains another image

As the title states I want to use ml (maybe some kind of CNN autoencoder?) to find the most similar image (I have a list of 10k+ images) within another image. I am currently just using opencv with ...
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0answers
6 views

How to understand Xgboost model dump

Noticed that spark xgboost does not have a API trees_to_dataframe() as that in Python API, I am trying to parse the getModelDump ...
1
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1answer
14 views

Slight confusion on the learning process

Hi guys I have a slight confusion on the learning process of neural networks. When the input layer receives inputs, goes through the hidden layers and then into the output layer. How does the neural ...
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0answers
19 views

Optimizing Decision Model with incomplete testset

I have a table of 2 features (numbers) on which I define a simple binary classification "model" (i.e. a simple logical expression) which needs 2 parameters thresholds. The model tries to ...
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0answers
13 views

Time series forecasting in Python with 2 categorical variables

What approach is the best for a time series forecasting where you want to include 2 categorical variables in python? Im not finding any useful information that can help guide me with this; mainly ...
2
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1answer
34 views

Multi-output, multi-timestep sequence prediction with Keras

I've been searching for about three hours and I can't find an answer to a very simple question. I have a time series prediction problem. I am trying to use a Keras LSTM model (with a Dense at the end) ...
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0answers
9 views

Algorithm to capture maximum number of points spread across the four quadrants

I was preparing for the data science interview questions and encountered the following problem: You are given some points in four quadrants and the points are fixed. You need to point the camera at an ...
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1answer
32 views

What's the issue with my code for visualizing linear regression in 3 dimensions with matplotlib? [closed]

I am trying to use linear regression that takes two variables "Idade" and "LF" and tries to predict a third one, "DGAF". I'm trying to both do the scatterplot with the ...
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0answers
12 views

Why is the posterior chosen to be normal in variational autoencoder?

Is there any reason for choosing the posterior $q(z|x)$ as normal distribution in variational autoencoder? or is it just for convenience?
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0answers
4 views

Inverse Autoregressive Spline Flow Implementation

I have to implement an algorithm for a university project, however I can not seem to wrap my head around it. The algorithm should be an inverse autoregressive normalizing flow using splines. It should ...
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0answers
7 views

Using a multi-headed neural network, how should I approach the regression head loss

I have a multi-headed NN where one head performs multi-label classification and the other a regression task on a set of images. The classification head outputs a one-hot vector where each value in the ...
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1answer
13 views

How does the random forest vote work?

I have a question. How is the voting done in random forests. I can't understand rationally, since we have a bootstrap sample drawn, and have built dection trees based on them, where is the new data ...
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1answer
9 views

What's the default Scorer in Sci-kit learn's GridSearchCV?

Even if I don't define the scoring parameter, it scores and makes a decision for best estimator, but documentation says the default value for scoring is "None", so what is it using to score ...
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1answer
11 views

Criteria for saving best model during training neural network?

I am doing 4-class semantic segmentation with U-net using generalised dice loss as loss function. General approach to save best model during training is to monitor validation loss at each epoch and ...
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0answers
17 views

StratifiedShuffleSplit

I deal with a cars data, but the data is non representative, there is a huge number of some cars and small number of other car as follows: ]1 I am using ...
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0answers
12 views

Hidden Markov model (HMM) package in julia? [closed]

I would like to know which is the fully stable HMM package in juli
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0answers
9 views

Which statistical tool, for test of hypothesis, is appropriate to find p- value in a python time-series data? [closed]

I have a long-term timeseries dataset with hourly time resolution. I found daily average values for each day in a week. I could clearly see some weekly variation. But, I want to ascertain that the ...
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0answers
5 views

Problem with elastic constraints in PuLP

(This is my first question on Stack Exchange) I am working on a production allocation problem, whereby sales orders have to be allocated over three production plants. I am using PuLP in Python, and ...
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0answers
27 views

How does shuffling make data identically distributed?

It makes sense that gradient descent algorithms (like stochastic GD, mini batch GD) work better when we shuffle data. (It makes instances in a dataset independent) (...
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0answers
10 views

How to make fair comparison of multi-task RL models if I have unlimited test data?

The data comes from a simulator hence I have the possibility to generate unlimited data. The reward is 0 (no success) and success(1) if episode is successful. Now, the question is what metric to use ...
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0answers
4 views

How to Normalize image intensities of CT and MRI images (single channel)

I have data-set which contains MRI and CT images and all of them are labeled. I want to create MRI-CT classifier. But intensity range of MRI and CT are different. CT ranges between (-1024 and 2000) ...
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0answers
24 views

XGBoost failing on highly imbalanced data!

I am working on a classification problem, where I am trying to predict a fraud login. The data is highly imbalanced i.e. 0 = non fraud logins , 1 = fraud logins 0 : 4538076 1 : 365 I have been trying ...
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1answer
24 views

reprocessing steps for images before training classification models

I have a data set of images for classification task. I read some articles about image reprocessing (before training CNN models) ...
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1answer
19 views

Random Forest but keep only leaves with impurities below a threshold

Is there an algorithm out there that creates a random forest but then prunes all the leaves that have an impurity measure above a certain threshold that I would determine? In other words, if I set min ...
1
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0answers
21 views

Understanding model's learning curves

I'm trying to train a Lane Detection CNN called PINet on a proprietary dataset. Below are some of the important configuration values: Batch size: 6 Optimizer: Adam Learning rate: High of 1e-4 and Low ...
1
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0answers
21 views

how to use CNN-LSTM with timedistributed

I am trying to use CNN-LSTM model with keras to reconstruct the time-series images, but now there are some weird problems. The input image is gray-scale and the input shape is ...
0
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1answer
21 views

in binary classification where class labels are {-1, 1} is preprocessing needed?

In machine learning we convert labels using LabelEncoder to convert string ex:{"malignant", "benign"} -> {0, 1} I am wondering if converting Labels to any other numbers matter, ...
0
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1answer
19 views

Is this a tried alternative to word embedding for NLP?

I'm searching for research related to my idea, but apparently cannot articulate it well enough to the search engines to show me what's been published on this. My idea: in a deep learning context (text ...
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0answers
9 views

Minimising inputs for decision tree predictions

It is common for decision trees with asymmetrical shapes to have leave nodes that come early. For example, the model can already generate a prediction if the answer to the first question is FALSE, ...
0
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1answer
14 views

Neural network activation function [duplicate]

im fairly new to neural networks. I want to ask what exactly does the activation output, is it the probability the combined summation of inputs and weights lead to a match for the next neuron? Thanks
0
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1answer
19 views

when will the mlp give constant prediction?

I have a regression task.(to predict price for finanical market) I build a mlp to do the regression. I found mlp will stop at giving a constance prediction. which i think it's useless. Does this mean, ...
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0answers
13 views

computer vision or machine learning disasters [closed]

overfitted models can often have terrible outcomes. We saw one news where a woman was killed by a self driving car. However, that was the only exam I have read about. Have there been any other major ...
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0answers
13 views

Performance metrics for balanced binary classification

From my understanding the reason we use Confusion matrix, Precision-recall, F1 score is because when our datasets consists of imbalanced class labels accuracy can be misleading. However what if ...
0
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1answer
10 views

Reducing features to 2 by PCA confusion Matlab

I am trying to reduce $500$ features to $2$ as an assignment. I wrote the following code and I am deeply concerned if it is true as when I plot it on the graph it does not look good. It should look ...
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0answers
12 views

How can I get accuracy of a predicted value specifically in Python?

I am currently working on a disease prediction machine learning model. I used Random Forest Classifier in my model, and now I am trying to get probabilities or accuracies of predicted values, but the ...
0
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1answer
15 views

How do I replace NaN values using group by pivot_table in pandas DataFrame?

I am working on a machine learning practice problem, from https://datahack.analyticsvidhya.com/contest/practice-problem-big-mart-sales-iii/#ProblemStatement I want to replace the null values in the ...
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0answers
5 views

Multi Input Network MNIST-CIFAR10

I have the following task of meta learning: We want that our neural network learns to sum weights. 1)Do the training on MNIST, and on CIFAR10 (as support dataset). We want that performance (accuracy) ...
2
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1answer
39 views

Basic doubt regarding “training” of a YOLO model

So I have just recently started exploring machine learning, and for a project I was required to train the YOLO v5 model. I first tried it on the coco128 dataset:https://www.kaggle.com/ultralytics/...
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0answers
31 views

AB testing for Recommender models

Let's say that I have two recommendation system models built, Model A and Model B. Now I track the performance of both the models for 5 days from 1st Jan to 5th Jan. Each model has been assigned a ...

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