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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32
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4answers
66k views

When to use Random Forest over SVM and vice versa?

When would one use Random Forest over SVM and vice versa? I understand that ...
1
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2answers
2k views

Dealing with multiple distinct-value categorical variables

So, I've got a dataset with almost all of its columns are categorical variables. Problem is that most of the categorical variables have so many distinct values. For instance, one column have more ...
1
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0answers
6 views

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 ...
0
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1answer
45 views

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, ...
0
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0answers
15 views

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 ...
1
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0answers
18 views

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 ...
0
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1answer
418 views

Spacy Text classification (Binary Classification)

I have a dataset of two folders. One of them contains the documents(text, pdfs) related to personal information (like name,email,address etc), the other contains non-personal information. I have to ...
2
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0answers
15 views

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 ...
3
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1answer
975 views

How to load numerous files from google drive into colab

I am trying to load in 30k images (600mb) from Google drive into Google Colaboratory to further process them with Keras/PyTorch. Therefore I have first mounted my Google drive using: ...
1
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1answer
94 views

scale_pos_weight using XGBoost's Learning API

I see it is possible to add a weight for unbalanced problems in XGBoost's Scikit-Learn API through scale_pos_weight. Does it have an equivalent in the Learning API? If not, is there a reason behind ...
16
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5answers
11k views

In the context of Deep Learning, what is training warmup steps

I found this term "training warmup steps" in some of the papers, what exactly does this term mean? Has it got anything to do with "learning rate"? If so, how does it affect?
6
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3answers
1k views

What are bias and variance in machine learning?

I am studying machine learning, and I have encountered the concept of bias and variance. I am a university student and in the slides of my professor, the bias is defined as: $bias = E[error_s(h)]-...
0
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2answers
53 views

Bias and variance in the model o in the predictions?

This topic confuses me. In the literature or articles, when talking about bias and variance in automatic learning, specifically in cross-validation, do they refer to the high bias (underfitting) and ...
2
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1answer
3k views

Agglomerative Hierarchial Clustering in python using DTW distance

I am new to both data science and python. I have a dataset of the time-dependent samples, which I want to run agglomerative hierarchical clustering on them. I have found that Dynamic Time Warping (...
2
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1answer
25 views

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, ...
6
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1answer
202 views

Training stateful LSTM with different number of sequences

I'm using a stateful LSTM for stock market analysis, and I have varying amounts of data for each stock, ranging from 20 years to just a few weeks (i.e. for newly listed stocks). I use 3 years of data ...
0
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1answer
409 views

Object detection model using images which have single instance of class per image-can it detect multiple instances in a single image?

I tried to train Faster R-CNN to detect multiple instances of a single class (eg. pomegranate on a pomegranate tree) but the training data consisted of 200 images where each image had only one object ...
0
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0answers
10 views

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 ...
0
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1answer
1k views

Is it possible feed BERT to seq2seq encoder/decoder NMT (for low resource language)?

I'm working on NMT model which the input and the target sentences are from the same language (but the grammar differs). I'm planning to pre-train and use BERT since I'm working on small dataset and ...
0
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0answers
7 views

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 ...
0
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0answers
13 views

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 ...
0
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0answers
18 views

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, ...
1
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1answer
24 views

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 ...
1
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1answer
25 views

Scoring metric for recommendation system

I'm working on a project that involves building a news recommendation system. I've come as far as quantifying user interaction with different articles on the site into user's affinity towards atopic ...
1
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1answer
80 views

How to use text as an input for a neural network - regression problem? How many likes/claps an article will get

I am trying to predict the number of likes an article or a post will get using a NN. I have a dataframe with ~70,000 rows and 2 columns: "text" (predictor - strings of text) and "likes&...
2
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1answer
228 views

Convolution neural network with 11 million parameters unable to overfit on 100 image samples

I have been trying to do some sort of image enhancement on grayscale images. I have used both pixel wise loss and perceptual loss (perceptual loss uses classifier between 2 classes trained on the same ...
1
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1answer
16 views

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 ...
8
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2answers
26k views

cosine_similarity returns matrix instead of single value

I am using below code to compute cosine similarity between the 2 vectors. It returns a matrix instead of a single value 0.8660254. [[ 1. 0.8660254] [...
1
vote
1answer
31 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. ...
0
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0answers
5 views

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: ...
0
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2answers
151 views

huge doubt on anomaly detection

from the naked eye itself, we can tell in the region 5161 the network usage is high so that is the anomaly in my case, then why do we want to apply k-means and other machine learning algorithms to ...
2
votes
1answer
147 views

Is it feasible to use decision tree algorithms for sensor fault detection?

The gist is me wanting to separate system faults from sensor faults given some dataset from a wireless sensor network using a machine learning algorithm. For instance, if I have some temperature ...
0
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0answers
8 views

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 ...
0
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1answer
123 views

The distribution of dataset train and test are the differents, how to fix this?

I am new in data science and like some help to understand my problem. For instance, I have two signals non-stationary for the same condition (figure 1). I acquisition them at different times(in the ...
0
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0answers
24 views

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 ...
1
vote
2answers
125 views

How to treat the undefined values which make sense?

I'm currently trying to create a few features to improve the performances of a model. One of those features that I would like to create corresponds to the difference in days between a customer's ...
0
votes
1answer
66 views

Comparing Dataset - Should I use the same Test dataset?

I am training ML CNN model. I want to compare different images dataset. The dataset all have different characteristics (Translated or not, Rotated or not, etc.). I do not modify the ML model between ...
2
votes
1answer
121 views

calculation of average ROC in IMageNet paper?

The IMageNEt paper Image Net. presents the Average ROC curve for the 16 classes in the imagenet data, visit image figure. 8 in the paper. what is the known function to compute this ROC plot. As ROC ...
2
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1answer
3k views

Variational Autoencoder TIme Series

Can anyone suggest a blog where Variational Autoencoder has been used for time series forecasting?
2
votes
2answers
693 views

normalization/denormalization for linear regression problem

My question is simple actually, I have two features that have big difference in scale. So I used a simple normalization by dividing the scale=np.max(array) for both data and lables. Then after ...
0
votes
1answer
10 views

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 ...
0
votes
1answer
191 views

Data Augmentation for Regression ANN with low Sample Size

There is a Dataset of 65 tuples. I want to Augment new Data from this set and validate my ANN on the original Data. Is there a possibility, that my ANN already overfits on the augmentet Data. For ...
2
votes
1answer
66 views

How do i create a classifier on sensor data?

I am working on a indoor localization based on magnetometer. I have 9 separate time-series datasets of sensor readings taken from coordinates 00, 01, 02, 10, 11, and so on until 22. Basically I am ...
3
votes
2answers
986 views

Weighted k nearest neighbor search

I've searched quite a bit and haven't landed on any useful results. The problem statement is: Given a set of vectors, I wish to find its approximate k-nearest neighbors. The caveat here is that each ...
-1
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0answers
21 views

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
2
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1answer
50 views

How to decode encoded labels in Decision tree classifier

I have some dataset with procurements of organization where actually i'm working. The aim is to find most important features that describe why some processes of purchases is succesful, and why not ...
2
votes
1answer
154 views

Classification followed by regression to handle response variable that is usually zero

I have a data set consisting of a bunch of predictors (mostly unbounded or positive real numbers) and a single response variable that I wish to predict. The response is typically exactly zero -- ...
5
votes
1answer
95 views

Predicting change of shapes/coordinates

I'm trying to find a way to predict/calculate how a shape (e.g. outline of a glacier) will change in the future—based on its history (previous shape) and additional factors (e.g. Δtemperature). In my ...
2
votes
1answer
14 views

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.
1
vote
1answer
42 views

Is a dense layer required for implementing Bahdanau attention?

I saw that everyone adds Dense( ) layer in their custom Bahdanau attention layer, which I think isn't needed. This is an image from a tutorial here. Here, we are just multiplying 2 vectors and then ...

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