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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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6 views

Machine Learning Model Input and Output Flow

I am working on a backend for structuring and submitting data into a ML model. I have 3 questions regarding this process. What is the best method to feed the model continuous data (updated every 30m ...
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Is it possible to build ensemble models without decision tree?

I know that the description of ensembles itself suggests otherwise. However, I'm really new to ML and all the ensemble models I came through so far use/described using the decision tree.
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What is the best Classification Method alternative to Nominal Logistic Regression, if your Response and all Predictor variables are Categorical?

Hy, I need help in choosing the best classification method. My response variable is nominal with "4" categories and five predictor variables, two of them are nominal and three are binary. ...
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Machine learning accuracy for not a class-imbalanced problem

I would like know if the accuracy has an impact on not class-imbalanced dataset ? I know that accuracy is sensitive to class-imbalance and also always good to be able to appreciate precision and ...
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15 views

How to deal with Different Shapes of X_train and X_test after OneHotEncoding?

I am trying to perform OneHotEncoding as well as feature scaling on my training and testing data separately, steps I did: ...
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how to make Support Vector Machine Basic Algorithm/function in R

how to make function of Support Vector Machine in R
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Merging models: using a named entity recognition model to annotate data on a different dataset

Lets say we have two trained models Ma and Mb which were trained with different datasets in a Named Entity Recognition task. Those datasets A and B contain different document and also variables or ...
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Confusion matrix terminology

I am working on machine learning with a supervised problem with 2 classes: NO and YES, and I need some precision about confusion matrix. I read 2 differents terminologies, some writes matrix confusion ...
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Input Features of a Hierarchical Structure

I have input features of a hierarchical structure. Each feature consists of a header element and 0 to n subfeatures of the same structure. Also, there is no upper limit for n and n can be different ...
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18 views

How to visualize data after performing OneHotEncoding and normalization?

I have a dataset and on that, I have performed OneHotEncoding and Standardization using standard scalar, Now that I have preprocessed data I have to visualize it, but on converting it to pandas ...
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How to perform feature selection on a dataset using correlation-based feature selection process

I have a dataset and on that, I have to perform feature selection using a correlation-based feature selection process (using scikit-learn), can anyone please show me how to do it with a small example ...
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Making a row-wise convolutional layer in keras

I want to make a layer that is almost exactly the same as a Conv2D layer, but essentially has a kernel for each row of the image, so that each row of the output is generated by taking the dot product ...
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When Does Feature Selection Takes Place?

I have a dataset where there are categorical features as well as numeric features, and I have to perform OneHotEncoding, Normalization and feature selection on it. In what order should I perform these ...
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Feature input vector machine learning formula

I would like to formulate in maths equation my feature input vector X which is composed of 7 input features. Is that correct to write: $$ X = \sum_{i=1}^{n=7}x_{i}=\left \{ x_{1},x_{2},x_{3},x_{4},x_{...
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Keras: Custom output layer for multiple multi-class classifications

Hello, I’m quite new to machine learning and I want to build my first custom layer in Keras, using Python. I want to use a dataset of 103 dimensions to do classification task. The last fully connected ...
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23 views

Ways to impute missing data in higher quantity

Can someone tell me what would be best way to impute missing data in columns where there are more than 50% records missing. I cannot simply ignore those columns as that would lead to lose so much of ...
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26 views

Best Way to find the important features for the model

I have data with 245 Features and almost all of the features are categorical. I would like to know what will be the best approach to find the important features for training the model. I know I can ...
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How does Gradient Descent work?

I know the calculus and the famous hill and valley analogy (so to say) of gradient descent. However, I find the update rule of the weights and biases quite terrible. Let's say we have a couple of ...
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7 views

ValueError when upload pkl model file

I'm saving a .pkl file and, but trying to load it I get: ValueError: Buffer dtype mismatch, expected 'SIZE_t' but got 'long' The save and load methods: ...
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13 views

Differentiation of Learning Capabilities of Different Networks

I have a conceptual problem regarding the overall learning capability of a neural network differentiated by the different types of input that we can give to the network. Suppose that we have a ...
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8 views

Update function for NN with logistic and sofmax

Can anyone help me confirm my work or find resources on how to come up with the update function for each layer in the Neural Network for multi-class classification problem i.e I am using logistic as ...
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How are scores calculated for each class of binary classification

The formula for Precision is TP / TP + FP, but how to apply it individually for each class of a binary classification problem, For example here the precision, recall and f1 scores are calculated for ...
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1answer
19 views

Difference between ReLU, ELU and Leaky ReLU. Their pros and cons majorly

I am unable to understand when to use ReLU, ELU and Leaky ReLU. How do they compare to other activation functions(like the sigmoid and the tanh) and their pros and cons.
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26 views

scikit-learn OneHot returns tuples and not a vectors

First I do a label encoding to all the columns that are strings so they will be numeric. After that, I take just the columns with the labels, convert them to np array, reshape, and convert them to one-...
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Assess the goodness of a ML generative model (text)

Take a RNN network fed with Shakespeare and generating Shakespeare-like text. Once a model seems mathematically fine, as can be assessed by observing its loss and accuracy over training epochs, how ...
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How to reduce RMS error value in regression analysis & predictions - feature engineering, model selection

There's this dataset containing the metadata of Twitch's top 1,000 streamers of 2020. You can have the details here. I am currently participating in a challenge to predict the values for Followers ...
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Which algorithm works well for forecasting sales prediction and the reason to choose particular algorithm?

I am working on a project 'Rossmann Sales prediction', in which I have to forecast the sales of Rossmann Stores. So it is a supervised ML problem. I applied random forest. But then in interviews ...
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How to use the eval set in catboost appropriately?

Let's say you have a dataset, and you split it into 80% training and 20% testing. Naturally, you want to find the optimal hyperparameters for your model, so with the training set, you plan to do cross ...
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Which ML algorithm is best works on text data and the reason behind it? Also, which metrics is used for testing performance of model?

I am working on a project - 'sentiment analysis of tweets.' There are 5 different sentiments - extremely negative, negative, neutral, positive, and extremely positive. So it is basically the NLP ...
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Is there any mathematical basis for distributed training of a neural network on multiple machines?

Let us say that I have 50 people download a program that engages in supervised training of a neural network I designed. The data samples being provided are pretty random and the correct outputs are ...
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How do I split correctly split my dataset into train, test and validation?

I'm attempting to split my data set into 70% training, 15% testing and 15% validation. ...
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Loading medical imaging data from multiple folders

I have a fairly basic mathematical and implementational understanding of ML algorithms and CNNs, and I am trying to think of an approach for this task: https://www.kaggle.com/c/rsna-miccai-brain-tumor-...
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How does the model trains with a 'Multinomial' parameter in Logistic Regression (Scikit-learn library)

I try to understand how the 'decision boundaries' are drown in a colored plot for a 'multinomial' parameter and then, how the model gives the prediction for a particular class. It can be assumed that ...
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1answer
20 views

Understanding SVM's Lagrangian dual optimization problem

I was going through SVM section of Stanford CS229 course notes by Andrew Ng. On page 18 and 19, he explains Lagrangian and its dual: He first defines the generalized primal optimization problem: $$ \...
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Answering the question of "WHY" using AI?

We have seen lots of natural occurrences that are happening in the whole world. Since we have great progress in technology and in particular AI, How can I employ <...
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Trained model performs worse on the whole dataset

I used pytorch as the training framework and the official pytorch imagenet example to train the image classification model with my custom dataset. My custom dataset has 2 different label (good and bad)...
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I am attempting to implement k-folds cross validation in python3. What is the best way to implement this? Is it preferable to use Pandas or Numpy?

I am attempting to create a script to implement cross validation in data. However, the splits cannot randomly take any records, so the training and testing can be done on equal data splits for each ...
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Best Practices For Dealing With This Scenario

I'm presently building a spam classifier. The model is unable to even overfit the training set at present. To investigate, I plotted the distributions of the model's features, and compared them across ...
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Best Approach for Predicting NFL Betting Outcomes

I play a game every year with my family, where we compete to make picks against the vegas odds for each NFL game. We aren't actually betting any money, but instead we each try to make the most correct ...
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1answer
21 views

Does BERT need supervised data only when fine-tuning?

I've read many articles and papers mentioning how unsupervised training is conducted while pre-training a BERT model. I would like to know if it is possible to fine-tune a BERT model in an ...
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1answer
26 views

What is the meaning of the Gini Index?

I'm studying random forest models, but I don't understand what the Gini index is and what it's for. Does anyone have any material on this or can give me an explanation? Thanks!
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1answer
26 views

Multiple AUCs in R

I've been using an interpretable machine learning package for binary decision trees known as IAI. Long story short: the core method here is known as an 'optimal classifier' (it does not use greedy ...
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1answer
15 views

Understanding Lagrangian equation for SVM

I was trying to understand Lagrangian from SVM section of Andrew Ng's Stanford CS229 course notes. On page 17 and 18, he says: Given the problem $$\begin{align} min_w & \quad f(w) \\ s.t. &...
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1answer
12 views

Creating and training a Multilayer perceptron model with few data

Are there any ways to create a deep multilayer perceptron model that is capable of making accurate regression predictions based on the training done using around 1000 unique data? I'm currently ...
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63 views

ML : Found input variable with inconsistent numbers

I am trying an Retail ML project, but am stuck on the Error "Found input variables with inconsistent numbers of samples: [982644, 911]". I tired many thing & I know why this error occurs,...
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3answers
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Should deterministic models be trained splitting into train, test datasets?

I'm studying the difference between GLM models (OLS, Logistic Regression, Zero Inflated, etc.), which are deterministic, since we can infer the parameters exactly, and some CART models (Random Forest, ...
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Forecast Model to Estimate Customer Service Call Volume and Appropriate Staff

I am working on a project to predict the proper staffing needed for a customer service team using historical data. I am new to machine learning, and I am not sure if my approach to this problem is the ...
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8 views

How to do Interpretable AI with multiple image input fields and a single real-valued output image?

I have input data of the shape: (num_ex, num_features, 64, 64) and real-valued output data of shape: (num_ex, 1, 64, 64) I ...
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Can Adagrad or Adam be used in loss function with l1-norm regularization?

there is one question for me. I want to know that how Adam or Adagrad treat l1-norm regularization in loss-function? (e.g. Lasso) I know that l1-norm is not differentiable function at zero but we can ...
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How to model prior informaton in sequential models?

Are there any approaches to model prior information in sequential models? Such as in Sequence classification. For example, I have an input sequence [[Z, 0, 1], [Y, 1, 1]]. I need to classfy this into ...

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