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Questions tagged [classifier]

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What to do if I have a very low metric on one of the classes during multiclass classification?

I trained multiclass text classififer with fasttext. I have a very low metric on one of the classes. Here are results of metrics for each class on test data: ...
user162857's user avatar
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how to get feature importance on unseen test data

I trained a random forest classifier with a set of features and saved the model. (the features were selected based on their correlations with the response variable. Only those features with ...
Tamanna Mostafa's user avatar
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1 answer
60 views

What do the terms in this equation $$θ1x1+θ2x2+θ0=0$$ represent?

I am currently learning ML from a course by MIT. I am from a non tech background and unable to understand some equations shown in this lecture of Linear Classifiers: https://youtu.be/yOKDzd73KgM?t=57 ...
Steve's user avatar
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How to visualize a decision tree classifier?

I'm using ID3 algorithm to build a classifier and was wondering if there is any way to visualize the decision tree that the algorithm builds. This is my code for a decision tree in Python: ...
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2 answers
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Using a Genetic Algorithm in junction with a digit classifier CNN to create an "MNIST image generator"

I'm trying to use a genetic algorithm that optimizes a 28x28 matrix (its shape) to make it look like an image of the number 7 that could be found in the MNIST image dataset. My attempt is to basically ...
kal_elk122's user avatar
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1 answer
80 views

Ensemble method with Blackbox Classifiers

I have few pre-trained blackbox models that are used for classification tasks. I want to know what is the best way to combine these models into a single classifier that does not require any re-...
user_04248753498's user avatar
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2 answers
52 views

Is there no reason to ever use naive bayesian learning?

I found this slide in the university course on machine learning I am currently taking. The reasons seem sound but I have not found this confirmed anywhere everywhere I read that for certain types of ...
user154502's user avatar
1 vote
1 answer
40 views

ANN time series classification validation loss never decreases

Problem statement: E2E classifier Input: [7x3600] time series of physiological parameters recorded from a medical device. Output: I am trying to learn a binary classifier to determine if the device is ...
Ben K's user avatar
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What does "n∼1/d" mean?

Or rather, what is the "~" notation mean? For reference, I'm trying to understand this section from a sci-kit learn documentation page.
Maxim's user avatar
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1 vote
2 answers
85 views

How does a classifier work on categorical features?

I have a dataset with a categorical variable year which has the years:: 2015,2016,2017,2018,2019. What I am trying to understand is how does a classifier work on this feature? Let's take a decision ...
Ramin Salimi's user avatar
2 votes
1 answer
106 views

Using Latitude/Longitude and site ID in classification of daily air pollution levels

Assume that there is a very large dataset of hundreds of sites which contains only the PM2.5 level, the site ID, and the Latitude and Longitude as features. The independent feature to be predicted is ...
There's user avatar
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1 answer
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output F1-score instead of Accuracy

I have the code below outputting the accuracy. How can I output the F1-score instead? ...
Pedro Silvestre's user avatar
1 vote
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163 views

Find VC dimension of 1D data

...
Tuhin Dutta's user avatar
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21 views

How to determine which classes are easier to predict with a decision tree?

So, I'm trying to work with decision trees on Iris dataset. I've noticed by trying out different parameter (max_depth, leaves etc) that some of the classes are easier to predict (most of the trees ...
Anđela Todorović's user avatar
2 votes
4 answers
136 views

Predicting Disease Drugs

I have a dataset in the format: ...
Atom Store's user avatar
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0 answers
47 views

Credit scorecard model

Could anyone point me to a blog or content that talks about creating credit scorecards without logistic regression models? Instead, if we use an ensemble technique, such as random forest, how can we ...
Pavan's user avatar
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1 vote
1 answer
253 views

How is there an inverse relation between precision and recall?

What I know? Firstly, Precision= $\frac{TP}{TP+FP}$ Recall=$\frac{TP}{TP+FN}$ What book says? A model that declares every record has high recall but low precision. I understand that if predicted ...
achhainsan's user avatar
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1 answer
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What input for a combined model (3 nets)

I have this architecture, made of 3 NNs: In code: ...
CasellaJr's user avatar
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1 vote
1 answer
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Shared classifier for 3 neural networks (is this weights sharing?)

I would like to create 3 different VGGs with a shared classifier. Basically, each of these architectures has only the convolutions, and then I combine all the nets, with a classifier. For a better ...
CasellaJr's user avatar
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How can I Determine a Treshold According to the Precision and Recall?

I am gettin these precision and recall values from my classifier and I want to determine a treshold for the test data. How can I determine that treshold? Is these values enough or something else is ...
TarabydaVllasıCafcaflıAtArabsı's user avatar
1 vote
1 answer
25 views

Should we also include negative instance in cross-validation process of one-class classifiers?

For a one-class classifier to do text classification, only positive instances are used for training. However, in the cross-validation process to select the best hyperparameters, should we also include ...
LGDGODV's user avatar
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1 vote
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211 views

Algorithm to predict the best time to recall a client

Let's immagine I have a dataset of calls from a call center to clients. Each call has a lot of information like at what time it was made, duration, if it was answered or not, if the client purchased ...
Data_Driven's user avatar
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2 answers
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what happens when a decision tree can't be split into further unit values?

Suppose I have a dataset A B C D 1 1 1 0 1 1 0 0 1 1 0 1 1 0 1 1 Here A,B,C,D are my independent features and D is my dependent feature. Now if I make a decision ...
Hasibul Islam Polok's user avatar
1 vote
1 answer
46 views

Combining multiple probabilities from a classifier. Propagating probabilities

Let's say I have trained a classifier that classifies images of animals into 10 different classes. And let's say that I have 20 different images of a particular animal and because I know the ...
AstroAllie's user avatar
4 votes
1 answer
173 views

Selecting a boundary on a binary classifier to optimal precision and recall

I have a logistic regression classifier that shows differing levels of performance for precision and recall at different probability boundaries as follows: The default threshold for the classifier to ...
Sandy Lee's user avatar
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1 vote
0 answers
35 views

Inferring composition of a subset of classes of multiclass dataset

I've come across a problem in assessing the design of a Machine Learning solution I am involved in, which I will describe using a commonly known dataset, the Iris Dataset, and some drawings. Suppose ...
John Karkas's user avatar
6 votes
1 answer
723 views

XGBoost skews towards minority class

I have a dataset with 85k positive labels and 53k negative labels. For this use-case, I am trying to maximize my efforts to the negative class (accurately identify true negatives, and minimize false ...
Nick Bohl's user avatar
0 votes
1 answer
69 views

Dropping attributes leads to better classifier accuracy? (Titanic Set)

I am currently tackling the Titanic Dataset on Kaggle. The goal is to find a classifier that can predict whether a passenger will survive or die. The dataset has features that I believe are strongly ...
Leon's user avatar
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2 votes
1 answer
405 views

Question about reshaping array size for KNN Classifiers

I keep trying to run a new set of data through my KNN Classifier but would recieve the message: ValueError: query data dimension must match training data dimension ...
LeeAnn Capistran's user avatar
1 vote
1 answer
69 views

ANN Classifier for extracted discrete image features

I have a features extraction algorithm that works well to extract features from images. I want to develop an ANN to classify those images based on those features. I have extracted features in a csv ...
DevLoverUmar's user avatar
0 votes
1 answer
963 views

Naive Bayes vs Full Bayes model classifiers

I have a hard time to understand when Naive Bayes works better than Full Bayes. In general, i know that naive bayes does the assumption that features are independent given the class. However, if ...
oprezyzer's user avatar
1 vote
0 answers
122 views

Detecting punch type using CoreML Activity classifier

I’m trying to train an activity classifier (made by Apple) to detect with kind of punch is thrown during boxing training. Accelerations are taken directly from an Arduino Nano 33 using Bluetooth low ...
Andrea's user avatar
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1 answer
388 views

Discrete values as target variable

I have discrete values in the target variable(Exactly 13 different values in total) . When I am giving that as input to Random forest Classifier ,it gives error that input as continuous. And if I give ...
Chinti's user avatar
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0 answers
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How can I test my trained model on a completely new dataset? [duplicate]

Preface I have an annotated text dataset on hate speech. Simply put, the dataset consists of a column called text which includes a piece of text, and a column ...
Aventinus's user avatar
  • 213
3 votes
1 answer
60 views

What does these points mean in Naive Bayes?

I have two concept related questions related to Naïve Bayes. Naïve Bayes is robust to irrelevant features. What does this mean? Can anyone give an example how does the irrelevant features cancels out ...
akshit bhatia's user avatar
0 votes
1 answer
127 views

For the line $w^Tx = 0$, how do we know the direction of the vector $w$

On page 17/28 of Lecture 3: Linear Classification, why the slope of $w$ must be positive?
user8314628's user avatar
1 vote
2 answers
773 views

Difference between packaged sentiment analysis tools (TextBlob/NLTK) and training your own classifier?

I'm new to ML and training classifiers in practice, so I was just wondering what the difference was between the built-in sentiment tools of packages such as NLTK and TextBlob as compared to manually ...
David Andrews 's user avatar
2 votes
1 answer
96 views

Attitude to text mining and preparing tokens, irrelevant words, low accuracy

For purpose of quite big project I am doing a text mining on some documents. My steps are quite common: All to lower case Tokenization Stop list and stop words Lemmatizaton Stemming Some other ...
heisenberg7584's user avatar
1 vote
1 answer
68 views

Classification - Divide the interval (0 - 1] to lets say 100 classes and use each class to make a calculation

class-1 represents 0.01, class-i represents 0.01*i, class-100 represents 1.00. Thus, when the classifier predicts the class-y and it should have predicted class-(y+1) there is a small error so we can ...
E. Vasilopoulos's user avatar
0 votes
1 answer
52 views

Classification Model based on Ordered Features

I am trying to build a classifier for a specific card dataset let's say cards or no cards. I am using Mobilenet trained on the Imagenet dataset as my classifier and further training it on my dataset. ...
Deepak Sharma's user avatar
2 votes
2 answers
101 views

How can I do the correlation between two estimators?

I'm working with several estimators of all kind. Then, I want to stack these estimators, and the best is if they have low correlation between them. I suppose that the correlation method depends on ...
juanmah's user avatar
  • 131
1 vote
1 answer
387 views

Building document classifier based on keywords, what would be the steps?

I have a requirement of classifying documents(.doc files) based on the profiles. I have a csv file with data: ...
Rex5's user avatar
  • 135
1 vote
0 answers
31 views

Penalization term for unfairness

I am reading [1], where the researchers do a logistic regression, but add to the loss function the following penalization term for fairness $ R^{AVD}_{FP}(\theta; S) = \left\lvert \dfrac{\sum\limits_{...
robertspierre's user avatar
1 vote
0 answers
192 views

SVM/Naive Bayesian text classification on multiple features

I was building a text classifier which takes into account certain features of the text and classifies them into two - "Yes" or "No". I have trimmed the text, removed stopwords and have applied TFIDF ...
Jackdaw's user avatar
  • 111
0 votes
2 answers
48 views

Certainity of a classifier

How to build a classifier that by default will predict that it is for class 1, but if the classifier believes with 80 certainity that it belongs to 0, it will be classed as 0. How to check how certain ...
Oman's user avatar
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2 votes
1 answer
416 views

Difference in model performance measures of train and test data sets

I am using CART classification technique by dividing a dataset into train and test sets. I have been using Mis-classification error, KS by rank ordering, AUC and Gini as MPMs(model performance ...
Manu Vats's user avatar
0 votes
2 answers
464 views

How to deal with name strings in large data sets for ML?

My data set contains multiple columns with first name, last name, etc. I want to use a classifier model such as Isolation Forest later. Some word embedding techniques were used for longer text ...
Danny Abstemio's user avatar
3 votes
3 answers
401 views

Image Classification on non real images

I was wondering how image classifier networks perform on images that are not photographs. For example, if you were to feed a drawing of a car or a face to an image classifier that was only trained on ...
dadrake's user avatar
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1 vote
3 answers
729 views

How do two perceptrons produce different linear decision boundaries?

I'm trying to visualize how two perceptrons converge to two different decision boundaries (which is ultimately used to create the classifier for the non-linearly separable data). Source: https://tdb-...
ashar's user avatar
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2 votes
3 answers
1k views

Why is my training accuracy decreasing higher degrees of polynomial features?

I am new to Machine Learning and started solving the Titanic Survivor problem on Kaggle. While solving the problem using Logistic Regression I used various models having polynomial features with ...
Apoorv Jain's user avatar