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Questions tagged [machine-learning]

Methods and principles of building "computer systems that automatically improve with experience."

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2answers
31 views

Why split data into train and test in linear regression?

I am wondering how train and test set works in linear regression. If I train the data it will give me a line of best fit, say I for my train data I am using first 70% of dataset => first 70% of the ...
2
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2answers
50 views

logistic regression : highly sensitive model

I am a newbie to data science and ML. I am working on a classification problem where the task is to predict loan status (granted/not granted). I am running a logistic regression model on the data. ...
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0answers
12 views

How to concatenate many .psv files in google collaboratory?

I have a folder named 'training' in my local drive which has 20000 .psv files. I zipped it and uploaded to google collaboratory, with the upload option in the Files section. I unzipped it with the ...
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0answers
21 views

Cannot Obtain Similar DL Prediction Result in Pytorch C++ API Compared to Python

I have trained a deep learning model using unet architecture in order to segment the nuclei in python and pytorch. I would like to load this pretrained model and make prediction in C++. For this ...
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1answer
39 views

Which courses should I take in order to learn ML and AI? [closed]

I want to learn ML and AI so I want to know which courses(It would be nice if the courses were free) should I take in order to do that and in what order should I learn them. I want the courses to ...
7
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2answers
140 views

What are the disadvantages of having a left skewed distribution?

I'm currently working on a classification problem and I've a numerical column which is left skewed. i've read many posts where people are recommending to take log transformation or boxcox ...
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0answers
21 views

Very low probability in naive Bayes classifier 1

I have some training data (TRAIN) and some test data (TEST). Each row of each table contains an observed class (X) and some columns of binary (Y). I'm using a Python script that is intended to predict ...
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0answers
22 views

Accurately choosing a model with sequential data

The dataset I'm working on is mapping journeys - breaking them down into entry & exit coordinates, and entry & exit times, for each part of the journey. My goal is to predict the final exit ...
2
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1answer
35 views

Cost sensitive classification with individual cost

I'm currently sitting on a problem, where i'm uncertain if there is not a much simpler solution. I'm trying to train a DNN with a dataset for a classification task that should be cost sensitive. ...
2
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1answer
40 views

Determining if time series follows a pattern

I was wondering if anyone had any idea how to solve this problem. So basically I have a dataset where some person approximately comes at some regular interval and I don't know what that interval is. ...
3
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3answers
82 views

Which learning tasks do brains use to train themselves to see?

In computer vision is very common to use supervised tasks, where datasets have to be manually annotated by humans. Some examples are object classification (class labels), detection (bounding boxes) ...
0
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1answer
10 views

Will the features in the image (edge, color, etc.. ) impacts on the performance of the spherical k-means?

I am very new in Machine learning, I recently implemented the spherical k-means, but finally I found a interesting point from the result. I used four datasets, they are minst, cifar-10, fashion-minst, ...
2
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1answer
37 views

How to measure the similarity between two images?

I have two group images for cat and dog. And each group contain 2000 images for cat and dog respectively. My goal is try to cluster the images by using k-means. Assume image1 is ...
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0answers
8 views

Direct Feedback Alignment implementation

I'm interested in Direct Feedback Alignment . I found this great article about it but it lacks a complete Python implementation as it is left as an exercise to readers. Does anybody have a full ...
1
vote
2answers
49 views

Column With Many Missing Values (36%)

Hello this is my first machine learning project, I got a dataset with 18.000 rows and I have a column with 4244 values missing. I don't know why the values are missing since when it's appropriate ...
2
votes
1answer
59 views

Efficient self study plan

I am hoping for a bit of guidance from experienced practitioners / academics. I want to work through the Bishop ML book, but have minimal background. What is the fastest way to get the pre-...
6
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0answers
49 views

Strategies for handling unlabeled data which is slightly different from the labeled data

Suppose you have a dataset with the following properties: The number of samples is fairly large (~100K samples) There are ~150 contextual features and 1 feature consisting of a text-string (which can,...
0
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2answers
29 views

Learning curve of CNN model

I have a graph for a model on train accuracy and validation accuracy: But I'm having trouble interpreting it. By the way i interpreted, I would say it is of poor performance. But I would like to know ...
1
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1answer
13 views

How to set a newtwork with two objectives?

Suppose I have a x_train, y1_train and y2_train. I want to construct a network (such as ...
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2answers
23 views

Pros and cons of using the zscore of a dataset before normalizing it during feature engineering?

Normalization is a common feature engineering technique. However, this post used standardize(zscore) on the dataset before normalizing it. I think that would result in losing some of the information ...
1
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1answer
26 views

How to perform (modified) t-test for multiple variables and multiple models on Python (Machine Learning)

I have created and analyzed around 16 machine learning models using WEKA. Right now, I have a CSV file which shows the models' metrics (such as percent_correct, F-measure, recall, precision, etc.). I ...
4
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3answers
504 views

What are some good books on Machine Learning and AI like Krugman, Wells and Graddy's “Essentials of Economics”

I am a Logistics student. I like the book "Essentials of Economics" by Krugman, Wells and Graddy in that it is concise, easygoing and not only a beginners book (it gradually approaches advanced ...
0
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0answers
23 views

Developing a time to default regression model to predict the time to default

Background: I used XGBoost to develop a probability model to get a probability measure of a particular loan defaulting. The results are very satisfactory, now my task is to develop a time-to default ...
1
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0answers
36 views

Lasso implementation Drawback

Recently I've been trying to implement Lasso by myself in R, not using the "glmnet" package, and based on an article by Tibshirani I wrote a raw code to implement coordinate descent method, and it ...
2
votes
1answer
24 views

Dealing with biased binary classifier

My training data is weighed heavier on the '1' class, with about a 4:6 ratio. This outputs a classifier that is of 82% accuracy with an emphasis on the '1' class, which makes sense. ...
0
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1answer
87 views

Classify sensor data (multivariate time series) with Python's scikit-learn decision tree

i'm trying to apply scikit learns decision tree on the following dataset with the goal of classifying the data: sensordata: multiple .csv files every .csv file has multiple sensors (see here) each ....
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1answer
259 views

Why use Variational Autoencoders VAE insted of Autoencoders AE in Anomaly Detection?

I have read many papers that recommends using Variational Autoencoders over Autoencoders since they have a more probabilistic approach and the ability to use KL divergence on the latent dimension. But ...
2
votes
1answer
23 views

Is image sharpening a good idea for data augmentation?

I'm training segmentation networks and while the dataset is somehow decent (~5k images) I wanted to augment it, so far I'm trying: RandomFlip RandomRotate RandomBrightness changes RandomShadows Due ...
0
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1answer
30 views

what is filter and kernel_size? [closed]

For below line of code model.add(Conv2D(filters = 32, kernel_size = (5,5),padding = 'Same', activation ='relu', input_shape = (28,28,1))) Here, ...
2
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0answers
17 views

How to create a prediction interval with the fact that the residuals follow a specific distribution (in python)

I am looking at a software development pipeline where I am predicting the lead time of different products flowing through the pipeline. After applying a boxcox transformation on the lead time (...
0
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1answer
13 views

Amazon Cloud Image istance most suited for R data mining

I'm new to the field of machine learning, I always used my laptop for regular statistical analysis with no performance problems. Though lately I started programming with caret and I find myself stuck ...
1
vote
1answer
36 views

What kind of algorithm should I choose for this music classification system?

I have in mind a program for analyzing short fragments of music, categorizing them as "good" or "bad". This would be part of a larger program that searches for larger good phrases and whole pieces. ...
2
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0answers
29 views

Test RMSE of polynomial regression drops when using more variables?

I am testing polynomial regression for a data set of 50 variables and a sample size of 5000. I ordered the coefficients of the linear model from high to low and then made different models using the p ...
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1answer
19 views
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0answers
16 views

What is wrong with my Precision-Recall curve?

Hi, I found this: https://github.com/rafaelpadilla/Object-Detection-Metrics I prepared my data: ground-truth and prediction files with bounding boxes. but I got a very strange plot. What do you thing?
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0answers
17 views

How do I recommend items to out of training users based on its recent views?

I used Spark's ALS implementation of matrix factorization (Collaborative Filtering for Implicit Feedback) to train user and item embeddings. Since we have a lot of users in system, I had to sample ...
0
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2answers
39 views

Discrete Ordinal Classification with Probabilities

If I have classes 1, 2, 3 and 4. But, I also need the probability for each of the other classes. I'm currently using XGBoost for one-vs-rest classification, but that means we're losing information ...
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0answers
10 views

how to decide to use dropout without checking learning curve?

Suppose I have been using dropout value of 0.5 as it gives me the optimal value . How can I explain to use dropout without checking learning curve?
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0answers
30 views

Seq2seq model that gets as input a sentence and outputs the same sentence

I tried to implement a model that takes as input sentences, which are hate_tweets and outputs exactly the same sentences. For this reason, I gave Input to the encoder and decoder exactly the same ...
1
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0answers
16 views

What's the difference between ELM and NNAR?

I'm working with time series forecasting using the two techniques that involve neural networks, the Extreme Learning Machine and the Autoregressive Neural Network. Reading the two methodologies, the ...
1
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2answers
403 views

Machine learning testing data

I am new to machine learning and it might be a bit of a stupid question. I have implemented my model and its working. I have a question about running it on the testing data. Its a binary ...
0
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0answers
12 views

How to compute mAP?

I would like to compute mAP. I detect only 1 class. I know should create two array. Presicion array and recall array and plot Precision/Recall Curve (PR Curve). Max of Groud-truth bounding boxes: 4 ...
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0answers
8 views

Regression methods for multi-dimensional categorical input and multi-dimensional real-valued output?

I wonder if there are useful regression methods for multi-dimensional categorical input and multi-dimensional real-valued output. Could random forest be one of those?
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3answers
37 views

is it necessary for Artificial NN to be fully connected or only fully connected NN is called ANN?

is it necessary for Artificial NN to be fully connected or only fully connected NN is called ANN ?
1
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1answer
60 views

Sentence similarity using Doc2vec

I have a list of 50k sentences such as : 'bone is making noise', 'nose is leaking' ,'eyelid is down' etc.. I'm trying to use Doc2Vec to find the most similar sentence from the 50k given a new ...
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0answers
6 views

caret dummyVars on unseen data

I created my dummy variables, trained my model and tested it as below: ...
0
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1answer
33 views

What is wrong with my logistic regression implementation?

Recently, I implemented the LR algorithm in Python. The main part of the code is as following(I didn't use mini batch in my code. Instead, I use the whole batch to compute gradients every time): <...
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0answers
13 views

Reverse engineering on Xgboost model

I am doing experiments on https://www.physionet.org/challenge/2017/sources/ submission. I like one of the submission code, which use Xgboost to train the ...
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0answers
10 views

Robert hecht Nielsen step function

For Hecht Nielsen step function which library is used or equelent pyhton?? If anyone know about this,any help will be appreciated.