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Questions tagged [machine-learning]

Machine learning algorithms build a model of the training data. The term "machine learning" is vaguely defined; it includes what is also called statistical learning, reinforcement learning, unsupervised learning, etc. ALWAYS ADD A MORE SPECIFIC TAG.

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871 views

How to compare the accuracy of two different models using statistical significance

I am working on time series prediction. I have two data sets $D1=\{x_1, x_2,....x_n\}$ and $D2=\{x_n+1, x_n+2, x_n+3,...., x_n+k\}$. I have three prediction models: $M1, M2, M3$. All of those model ...
3
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3answers
1k views

How to select predictor variables for a classification model?

I am running a customer churn predictive model in r. My confusion is when I try different combinations of variables I.e. Removing some from the model, I get completely different results in terms of ...
3
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3answers
592 views

Combining one class classifiers to do multi-class classification

I am working on a 3-class classification problem. The classifier I'm using is Bayesian Networks which provides me with a classification accuracy of around 60%. When I do a two-class classification, I ...
2
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3answers
448 views

What the relation between a random variable and a sample (or dataset) in machine learning?

I'm having trouble with the machine learning vocabulary, especially with the concept of random variables. Given a sample $X$ (with features $x_1, x_2, \dots, x_n$) that you train your algorithm on (...
2
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3answers
312 views

Predict income based on partial day

I have a really interesting question for you: I have data of hourly income with segments like: day of a week, department, source, etc. I'm trying to build a model that looks on historical data, and ...
2
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3answers
1k views

More data, to counteract overfitting, results in worse validation accuracy

I am currently trying to classify clothes for my final project in school. My problem is that after I gathered more data, to counteract overfitting, the validation accuracy dropped from 60% to 45%. ...
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3answers
33 views

Building a binary classifier on uncertain 0's

When building models to predict probability of sales etc. Its intuitive to select customers who already have bought the product as training data for class 1 and customers who does not have the product ...
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3answers
1k views

Cross Validation with Preprocessing (Normalization, Discretization, Feature Selection)

I am now trying to evaluate my model with cross validation. My dataset contains some numeric and nominal attributes. Here, I carry out the following data preprocessing tasks: A. Normalization: Min-...
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3answers
27 views

Two logistic regression or one Softmax regression

The following question is from Geron's Hans-On Machine Learning book. Suppose you want to classify pictures as outdoor/indoor and daytime/nighttime. Should you use two Logistic regression or one ...
0
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3answers
103 views

How to interpret the result of Forecast in R

I am working on Daily time series forecasting starts from 1-1-2016 to 31-08-2018, For such long series I have used below approach to forecasting for next 30 days. ...
0
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3answers
431 views

Machine learning on small datasets

As a beginner at machine learning, I wanted to work on a small project in which the dataset has only 80 rows and 5 columns. The dataset I am working with is related to a medical condition, with 4 ...
0
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3answers
401 views

Prediction after PCA and K-Means

I have a data set with a large amount of features. I'm applying PCA on it in order to run it through K-means, to discover clusters in my data set. I'd like to know what is the best practice to make ...
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3answers
24 views

Pattern of multiple measurement device data

I am trying to find pattern between data from two different source. I have aircraft altitude data from GPS and pressure sensor. Both data reference is mean sea level. I found discrepancies between ...
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2answers
530 views

How is the ROC curve plotted in Viola Jones face detection paper?

I am reading paper by Viola and Jones. There they have used ROC curve to measure the accuracy of their classifier. https://www.cs.cmu.edu/~efros/courses/LBMV07/Papers/viola-cvpr-01.pdf Could someone ...
1
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2answers
192 views

To provide dimensionality reduction, 1x1 convolutions are used, before passsing them through a 3x3, or 5x5 convolution in an Inception module.

To my understading what a 1x1 convolution does is gives an embedding of the (i,j)th entry of the feature map along its depth. Besides here some dimensionality reduction is also done. How will the ...
1
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2answers
116 views

How can I train my deep learning model on another similar yet different dataset

I am doing semantic segmentation (multi-class classification of image pixels) using convolutional neural networks (CNN) in Keras. In particular, I am applying this to aerial images of crops (...
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2answers
115 views

Machine learning - PCA and KNN on rgb images are too slow

I work with python and images of tables (taken from above). My aim is to take a photo of a random table and then find the most similar tables to it in my database. Obviously, the main feature which ...
1
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2answers
97 views

Compare two datasets and wheather they agree

I have two datasets and they both have the same set of independent variables: 9 of them are on scale from 0 till 100 3 of them are categorical(1 with two types categories, 1 with three types of ...
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2answers
150 views

Feeding clusters to neural network

I have labeled GPS location data (lat,lon) for determining whether a trip is of a certain type. The location data consists of start and end points, in the format of lat,lon coordinates. A trip is ...
1
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2answers
434 views

Can we predict the categorical variable of the given dataset?

I have a dataset (3000 rows) as below, as one can see the dataset also contains few important string columns as Location,Country,Injury,Time. Can we predict the <...
1
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2answers
60 views

How do I cluster/group people together given their durations for an given event?

I am new to machine learning and do have a very large dataset for a set of 100 people over a period of 1 year. and the goal is to find out who are buddys based on their lunch times. I have the ...
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2answers
151 views

Normal Neural Network for Image 100X100?

Thank you in advance for any help at all. So, I have created a neural network using back propagation and sigmoid function. It seems to work for XOR and images with size of 28X28. However, When I ...
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2answers
131 views

Heterogeneous Domain Adaptation without training data from target domain

Are there any strategies to learn a model that can classify data from one domain using only data from a different domain for training? For example, suppose I have a bunch of data from two different ...
1
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2answers
90 views

Assumption behind few latent features in recommender systems?

I know in recommender systems you have a rating matrix and then you factorize this matrix into two matrices and then learn those matrices with gradient descent. In those matrices we specify the number ...
0
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2answers
33 views

Binary classification without training data

My goal is to classify students of an online course into two groups: "cheaters" and "non-cheaters". I have some features which can be useful (grade, number of videos watched, some actions with videos, ...
0
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2answers
36 views

Machine Learning Algorithm for Count or Visit data

I am trying to figure out a good approach to use some machine learning on doctor appointment data. I want to first do an unsupervised clustering to look for any natural structure within the data (...
0
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2answers
69 views

Splitting data into training, validation and test sets

I am currently comparing 3 classification methods on a data set (in R). To do so, I have run this over a loop (100 iterations). I have split my data into a training, validation and test set. The ...
0
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2answers
36 views

Which tools should I learn to use in order to forecast sales for each day?

I am trying to forecast sales for a company that runs a few stores. In many cases, I am pretty successful using some basic methods in Excel to forecast sales for every month, but I'd like to be more ...
0
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2answers
32 views

Problems with sampling with replacement for generating train, test, and validation data sets

When creating train, test, and validation data sets for machine learning, random sampling without replacement is done to create disjoint data set partitions. Is there anything wrong with using random ...
0
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2answers
31 views

What is the rule for deciding when to normalize Variables In pre-processing?

Some techniques, Like boosting For classification, Do not require The Variables to be normalized.For other techniques, Normalization seems very important How Do I know When I need to normalize My ...
0
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2answers
24 views

How can I predict the value after a point with a short time of data?

I have a customer's online data. I have data such as the number of items purchased by the customer, the number and number of keyword queries for the customer, the age of the customer, the residential ...
0
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2answers
267 views

1x1 convolution for inception module

When understanding inception module, I once saw the following statement from an online post. What's the calculation underline the "...
0
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2answers
26 views

Can a neural network work with support datawhich was not there while training?

I am giving a hypothetical example to convey my question. Suppose I want to train a neural network that abbreviates strings with a preset list of words that are likely to be present in full form of ...
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2answers
31 views

Learning Curves: Should the training set size be increased incrementally or Random Selection?

I am trying to write a bespoke learning curve function. I was wondering how is it usually implemented. When the size of the training set is increased - Is it normally increased by adding new samples ...
0
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2answers
33 views

Conditional independece iff joint factorize four variables

Im interested with a derivation as shown by by Zoubin Ghahramani in his article ' Learning Dynamic Bayesian Network' The whole objective was to prove P(Z, W|X,Y) = P(W|Y)P(Z|X,Y) ---- EQ 1 Given ...
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2answers
1k views

Comparing F1 score across imbalanced data sets

I am working with multiple strongly imbalanced binary data sets (# of majority class > 20x # of minority class). Although all the data sets are strongly imbalanced, the ratio of the classes differs ...
0
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2answers
151 views

What is single deep neural network?

What does single deep neural network means? I did an object detection project using tensorflow though I am certainly lacking in knowledge about how it works. I am new to machine learning and I've been ...
0
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2answers
149 views

How linear regression algorithm estimates values and draw line

I am learning Machine Learning. and going through some videos. In that one slide came which I am not able to understand (Attached below). This is related to Linear Regression. In second image, it ...
0
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2answers
72 views

Best suited algorithm for prediction of purchase or no purchase based on click stream data

Could anyone please suggest the best suited model to be used for the prediction if a customer who has visited the website will buy a product based on the click stream data.Also,it would be great if ...
0
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2answers
33 views

Would variables that don't differ between the two categories improve classification?

I want to build do classification to determines if a user will visit another page on the website before logging out. So it's making a binary prediction: last page or not last page. Would variables ...
0
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2answers
42 views

Quantify quality of multi label assignment

I am interested in quantifying how well a multi label assignment performs. E.g. given 3 coloured boxes red, green and blue, with 20 likewise coloured balls in each. A monkey is handed all the balls ...
0
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2answers
351 views

How does one know if normalizing is improves reconstructions in the task of auto-encoding?

I wanted to understand the performance on an algorithm in the auto-encoding task and compare understand if normalizing the data was a good idea or not and compare the performance when the data is ...
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2answers
158 views
0
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2answers
131 views

graph classification task - multi label?

I have a data set in graph format representing semantic connection between terms. The data set is divided into clusters, each with several labels (not unique, or mutually exclusive, no set number of ...
0
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2answers
52 views

Prediction of features given predictor

I am working on a problem where my objective is to predict y given some features x1,x2,x3,...x8,x9 I solved this problem using some statistical and machine learning techniques like regression, trees, ...
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2answers
32 views

Inferring on an unknown number of function approximation

I want to ask whether a procedure to do the following job exists (or whether it makes sense for it to exist). First, assume we have $k$ functions $f_1,...f_k$ that have the same domain and range. ...
0
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2answers
257 views

What's the best algorithm type for low-dimensional grouping

I'm looking for some advice on directions to head in a project I'm working on. Basically what I want to do is identify general (of varying size) groups in a 2-D grid of points belonging to one of ...
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2answers
60 views

Machine Learning, Imputing values that should be blank

Sometimes data sets contain variables that indicate the presence of an event and the value that represented the event. As an example say a teacher wants to predict the grades of his students. Some of ...
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2answers
49 views

What is the relation between the training time and the batch size?

In the deep learning process, especially SAR-ATR (e.g., generic object detection), is there any relation between the training time (speed) and the training batch size? Is there a paper related to ...
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2answers
48 views

how to analyze time series data and mark if single data is seasonal or not seasonal

I have data set as shown. It is daily sales data for 4 different product for almost a year. I aggregated the sales of product for each day into . I plotted sales of 4 product as per date and got this ...