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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Training on a single, random domain, per batch vs multiple domains per batch on a common task

Say I have multiple domains such that d_i is drawn from D=[d_1, d_2, ... d_K]. We have two options to train a CNN which equally ...
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In DQN, why not use target network to predict actual state Q values?

In DQN, why not use target network to predict actual state Q values, and not only next state q values? In doing a basic dq learning algorithm with nn from scratch, with replay memory, and minibatch gd,...
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Negative log-likelihood not the same as cross-entropy?

The negative log-likelihood $$ \sum_{i=1}^{m}\log p_{model}(\mathbf{y} | \mathbf{x} ; \boldsymbol{\theta}) $$ can be multiplied by $\frac{1}{m}$ after which the law of large numbers can be used to get ...
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Keras: ValueError: Input 0 is incompatible with layer lstm_1: expected ndim=3, found ndim=2

I am using Keras functional API to write an LSTM model but It throwing an error can somebody please help below is the code for the model the output shape is 65. I am using Keras 2.2.4 and TensorFlow 1....
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data science ideas for payment integrity in healthcare insurance

I am looking for new data science ideas for payment integrity (waste, fraud abuse) in healthcare insurance. Can you suggests some articles, links, blogs about metrics or ml techniques?
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How to configure null hypothesis or what's the null hypothesis when using sklearn?

I'm predicting how BMI, GDP, ... factors affect life expectancy. Firstly, I tried to select topK features. ...
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Accuracy on Validation and Test set, Overfit?

Just a quick question, I am building a ML model right now however I am receiving very similar (72.2 and 72.4 for example)% for both Accuracy and F1-Score on my Validation Dataset and my unseen Test ...
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104 views

What is Inductive bias

Bias in a neural network is an additional neuron to be fired i.e let $y=a+bx$ where a is bias term Do we have any difference between bias and inductive bias. How Inductive bias is helpful in ...
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feature Extraction with mobileNet visualization

I am trying to create a logical visualization regarding how feature extraction with mobile net works in ml5.js. There's a good explanation here: https://youtu.be/kRpZ5OqUY6Y With ml5, you use a part ...
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Machine Learning - Euclidian Distance Classifier exercise

I'm taking part in an elective subject at university which mainly focuses on the foundations of Machine Learning. Now we got our first exercise - this task should be done practically in any language (...
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Why does Adam optimizer work slower than Adagrad, Adadelta, and SGD for Neural Collaborative Filtering (NCF)?

I've been working on Neural Collaborative Filtering (NCF) recently to build a recommender system using Tensorflow Recommenders. Doing some hyperparameter tuning with different optimizers available in ...
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Choosing the size of the network for Neural Collaborative Filtering (NCF)?

I've been working on Neural Collaborative Filtering (NCF) recently to build a recommender system. After doing some hyperparameter tuning with various sizes for embedding and dense layers sizes, from ...
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Machine Learning Model for Time Series Forecasting

I am using Random Forest, SVM, and XGBoost models to nowcast/forecast an economic time series variable. However, I would like to extend these models to optimize/customize them for time series ...
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Alternatives with better GPU than Google Colab Pro

I am currently running/training MAchine learning models that are very GPU expensive, Google Colab Pro is not giving me enough GPU/RAM Is there any alternatives with better GPU and more RAM than ...
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Imbalance classes in Named Entity Recognition

I am currently working on a NER problem which attempts to extract 2 entities - place-of-interest(POI) and street from an address string in the Indonesian language. I used IndoBert (available here) and ...
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GPA prediction of college student

I have a dataset consist of 8 columns and 15600 rows with the following columns:- 1.Entry_academic_year which have 5 discrete value (2558,2559,2560,2561,2562) 2.Faculty (It is the faculty that ...
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Question on rnn

For recurrent neural network, it can handle time series data I get some question on its pratice. Consider below 10,46,44,2,4,5 (t1, t2,....) 10,46,44 =>2 46,44,2=>4 ... Input ( x_t1, x_t2, x_t3) In ...
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how to evaluate the performance of a recommender system with single recommendation

Say we have a recommender system in production which recommends 1 our of N items according to some internal algorithm f given inputs Xi for each user i, let's assume f is a black box model. We have ...
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Encoding entities with features of continuous values

Given a set of entities, I would like to predict the next in the sequence; for this purpose, I would like to use RNN. However, my first challenge is how to model the entities. A possible input ...
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GridSearchCV Decrease performance RF

Can Gridsearchcv params perform worst than default RF? RF with default values performs rmse_train=4886,r^2_train=0.84, ...
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What type of ANN architecture to choose?

I have N number of teachers each of which has an input feature vector (25 dimensional) consisting of positive numerical values for different quality of aspects (for example, lecturing ability, ...
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How does transform work?

I was looking at the source codes of MinMaxScaler on Github. I know that when you fit a preprocessing class to a dataset, it takes the data and prepares it for transformation. Let's say, I fitted ...
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1answer
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what does one Shot learning mean? do they only need one image to train for some new class detection?

Being new to deep learning I am somewhat struggling to grasp the idea of one shot learning. Let us say I have a class to detect which didn't exist in training dataset such as COCO or Image NET. Can I ...
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Tuning hyper parameters for different models with caretList

I'm trying to train an ensemble using the caretList function in the caret package. I'm using these models: ...
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Can I get some advices on inferencing people from upwards using Yolov5?

I'm trying to inference people from upwards and count them using Yolov5. I know the controversy between yolov5 and yolov4, but for me, Yolov5 is more easier and reliable to use, also the setup. I have ...
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32 views

Why we take $\alpha\sum B_j^2$ as penalty in Ridge Regression?

$$RSS_{RIDGE}=\sum_{i=1}^n(\hat{y_i}-y_i)^2+\alpha\sum_{i=1}^nB_j^2$$ Why we are taking $\alpha\sum B_j^2$ as a penalty here? We are adding this term for minimizing variance in Machine Learning Model. ...
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Predict on new data / Model Deployment

I do not undestand, how the deployment of a ML-model works in the reality. A given dataset needs to be mostly time pre-processed (for example One Hot Encoding). After will be a model cretead and ...
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Train and predict two labels in a single process

I have a python program that makes predictions using scikit-learn RandomForestClassifier. The label is called "default" and it's the default status of a ...
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Documentation For Data Science Graduation project [closed]

is there any suggestion for an excellent Documentation Template used to write an Data Science Graduation projects Thanks alot
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How to implement sequence to sequence models?

I have a dataset with patient demographics, diagnosis history, hospital visit dates, drugs consumed etc. All these events have time stamp information (except static info like demographics such gender, ...
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Found input variables with inconsistent numbers of samples: [11232, 5616]

I don't know what is the reason for the error please guide me and help me out. I am at a learning stage.
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1answer
18 views

Can you choose a binary feature matrix for a binary classification model

This may be a stupid, but, I am new to deep learning (and machine learning for that matter) and I can't seem to find any literature to help with my question. All I can see when Googling many different ...
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1answer
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What if Training and testing dataset comes from the same source?

I am working on a classification problem in which I have to distinguish between healthy and damaged plates. when I use the combination of k-means clustering and SVM algorithm together with 10-fold ...
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Multiple step prediction for non-time series

I have a public EHR dataset which contains info on a) lab tests b) diagnosis c) surgical procedures d) drugs prescribed etc Now, using the above data elements, I would like to predict the below a) ...
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How can I use transfer learning to predict height given age in Japan, using a model developed with USA data?

Suppose I have a (training) set of $n$ observation $\{(Y_i^{(U)},X_i^{(U)})\}_{i=1}^n$ of age $X_i^{(U)}$ and height $Y_i^{(U)}$ from people in the USA. Now suppose I also have a (test) set of $m$ ...
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Difference between classification problem and concept learning

"To ground our discussion of concept learning, consider the example task of learning the target concept: days on which my friend Aldo enjoys his favorite water sport" This is from the book ...
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How do I initialize a Hidden Markov Model when using MFCC features for speech recognition?

I have a personal dataset of 10000 audio files, each consisting a single spoken sentence. These files each have the transcribed text labels with them that I can use for supervised HMM training. Now ...
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How to correctly train CNN with patches taken by labeled images, if the source image contains both positive and negative samples?

I have patches (tiles) taken from very large histopathological images. These images are labeled as healthy (negative) or tumor (positive). If the image-level label is negative, then 100% of the source ...
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1answer
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Lower Variance vs. Higher Validation Scores

So I'm trying to compare between two models, say model(1) has training accuracy of 90% and validation accuracy of 86%, while model(2) has training accuracy of 87% and validation accuracy of 85%. Now, ...
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1answer
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Clustering 2D curves

I have a set of curves in 2D space each expressed as a set of (sampled) data points. Each set has more or less the same number of items - eventually I guess I’ll use binning to make sure the number of ...
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Run ML model on a distributed manner on dataframe rdd partitions

When running a logistic regression on a large dataset with repartition, how do we stitch the results of the each partition results back to a dataframe to analyze. ...
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Applying Sci-kit Learn's kNN algorithm to Fresh Data

While I was studying Scikit-learn's kNN algorithm, I realized that if I use sklearn.model_selection.train_test_split, the provided data gets automatically split ...
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1answer
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Why do we need to concatenate in a U-Net?

You might be familiar with the U-Net, a machine learning network deceived for image segmentation. It's basically an encoder/decoder network with some direct links between encoder and decoder segments: ...
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35 views

Training a model purely on weak labels

I have read a couple of papers now use rules-based system to create weak labels and then train a BERT-based model only using these weak labels. Both studies have reported better performances on ...
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Can RNN be replaced with non-recurrent classifier for Sequence Classification problem?

Setup: We have sequence of events that are not evenly spaced (not a time series). Length of the sequence is constant. Goal: Predict class of the event that is most probable to follow this sequence. ...
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Are there any deep learning models to forcast waveforms from waveforms?

I want to forcast waveforms from waveforms. Now I have collected the dataset. The input feature is a waveform, e.g.: input feature The out is also a waveform, e.g.: output feature Are there any ...
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How to predict multiple time points in future?

Let's say I have a database of customer's purchase history. So, my data has below info a) customer demographics such as age, gender, country etc. b) customer order history such as order_id, order_date,...
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Python Object Detection - Unable to generate mAP scores for trained models

I'm new to Image Recognition and decided to have a go at training a custom detection model using transfer learning with a pretrained YOLOv3 model - pretty much just followed the steps here: https://...
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What kind of non linear regression model to use when there is very low correlation between independent and dependent variable

I have a data set with one independent variable(X) and one dependent variable (Y). Since my dependent variable is continuous that's why I am trying regression modeling. As can be seen in the image ...
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What is the meaning of the bubbles / spikes in the shap values ​plot?

Here are an example of shap values plot from here. How to interpret the 'bubble' or 'spikes' on this shap values plot I highlighted in yellow color?

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