Questions tagged [classifier]

The tag has no usage guidance.

Filter by
Sorted by
Tagged with
1
vote
1answer
21 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 ...
1
vote
0answers
30 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 ...
0
votes
2answers
80 views

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 ...
1
vote
1answer
28 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 ...
3
votes
1answer
25 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 ...
0
votes
0answers
14 views

Validation fraction parameter of sklearn's Gradient Boosted Classifier in use with time series data

I'm looking at using sklearn's Gradient Boosting Classifier (GBC) to predict the sign of stock returns. My question is regarding the parameter "validation_fraction" used for early stopping. ...
1
vote
0answers
17 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 ...
6
votes
1answer
86 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 ...
0
votes
1answer
33 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 ...
2
votes
1answer
135 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 ...
1
vote
1answer
29 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 ...
0
votes
1answer
151 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 ...
1
vote
0answers
62 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 ...
1
vote
1answer
39 views

Dicsrete values as taget 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 ...
0
votes
0answers
36 views

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 ...
3
votes
1answer
44 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 ...
0
votes
1answer
33 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?
1
vote
2answers
471 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 ...
2
votes
1answer
35 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 ...
1
vote
1answer
28 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 ...
0
votes
1answer
33 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 Imagenet dataset as my classifier and further training it on my dataset. I am ...
1
vote
2answers
26 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 ...
1
vote
1answer
69 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: ...
1
vote
0answers
23 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_{...
1
vote
0answers
153 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 ...
0
votes
2answers
41 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 ...
2
votes
1answer
154 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 ...
0
votes
1answer
57 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 ...
1
vote
3answers
411 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-...
2
votes
2answers
453 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 ...
2
votes
0answers
30 views

Correct approach to usage of class labels in cell imaging data

As part of a group project at university, we are given a series of videos of cell cultures over a 24 hour period. A number of these cells (the "knockout" cells) have had a particular gene removed, ...
4
votes
2answers
10k views

How do I get the feature importace for a MLPClassifier?

I use the MLPClassifier from scikit learn. I have about 20 features. Is there a scikit method to get the feature importance? I found clf.feature_importances_ but it seems that it only exists for ...
8
votes
2answers
8k views

When should I use StandardScaler and when MinMaxScaler?

I have a feature vector with One-Hot-Encoded features and with continous features. How can I decide now, which data I shall scale with StandardScaler and which data scale with MinMaxScaler? I think I ...
-2
votes
1answer
22 views

Converting int list to vector list

I want to train a text classifier using OnevsRestClassifier, but have problem getting a propper y. Currenly my y is a list of int, but I need it as a list of vectors. My y: ...
0
votes
2answers
103 views

Would a decision tree classifier be applicable here?

File from a situation where it is required to predict today’s stockprice from the stock prices of the previous three days: Could you use a decision tree classifier for this task? Why or why not?
0
votes
2answers
3k views

Always getting value one for a binary classifier

I'm using keras. I have one classification problem. The output should be either 0 or 1. I trained my model and I'm getting 86.59 accuracy. But when i check the predicted output what I'm seeing is all ...
1
vote
0answers
10 views

What happens if I do not encode the lables or classifiers in the data? [closed]

I have a data where the three variables are numerical and one variable is a string. I am using the simple decision tree algorithm. Read somewhere that the data in strings must be encoded with one hot ...
4
votes
3answers
4k views

How to handle “unknown” category in machine learning classification problems?

Tutorial problems come in the form of binary or mult-class classification where data are all properly labelled. In real-life applications, there are incoming data that do not belong to any category ...
2
votes
2answers
70 views

Support Vector classifier perform well with input features rather than transformed features in contrast to ANN-BP, random forest (other classifiers)

I am working on stock data with 5 raw features (OHLCV). Using few transformations used by technical analysts, have created 20 more features giving different kinds of indications. When trying to ...
1
vote
1answer
19 views

Adding the input layer - units with a decimal

I took the course Machine Learning A-Z from Udemy and am trying to apply what I learned in the tutorials. Theye taught us in the "Adding the input layer" portion of an ANN that the units is based off ...
2
votes
1answer
74 views

What can I use to post process an NLP tree generated from the python library `spaCy`?

Using spaCy as the NLP engine for a chatbot, I call nlp("Where are the apples?").print_tree() and receive: ...
2
votes
1answer
438 views

Class Imbalance Problem

I'm making a multiclassifier model with 5 classes. (it is not important in my question whether it has 2 classes or 5 classes, though). class distribution is very imbalanced. So, I did resampling for ...
6
votes
3answers
70 views

Classifier that optimizes performance on only a subset of the data?

I'm working on machine learning problem where I'm only interested in getting high accuracy within a narrow band of my predicted likelihoods. Specifically, I want an algorithm that will score very ...
4
votes
1answer
4k views

Distinguising features of linear vs, non-linear machine learning models (algorithms) [closed]

What are some examples of linear and non-linear machine learning models (algorithms) for purposes of comparison between the two categories? Which are the parameters (or scalars in a linear algebraic ...
15
votes
1answer
49k views

Train Accuracy vs Test Accuracy vs Confusion matrix

After I developed my predictive model using Random Forest I get the following metrics: ...
4
votes
1answer
3k views

One hot encoding of target space

I had a face to face interview for a data scientist job a few days ago. One of the questions I was asked was: in the case of classifier predicting the brand of TV from some features (price, size, ...
0
votes
3answers
2k views

In layman terms, what is the meaning of fitting a model into a data set?

When we fit any model into a data set for prediction, what exactly happens behind the scenes? I am learning Regression and I am a little confused about how exactly it fits the classifier or ...
1
vote
2answers
812 views

ROC curve shows strange results for imbalanced dataset

I have a classifier with a heavily imbalanced dataset (1000 of each negative label for each positive.) I'm running a GradientBoostingClassifier with moderate success (AUC .75) but the curve has this ...
1
vote
0answers
47 views

Need to calculate derived metrics in a classifier

I have a classifier that predicts a class given roughly 100 datapoints. The classifier that tends to perform best on my data is RandomForest. I have a lot of metrics such as revenue for each of the ...
0
votes
1answer
70 views

In R, can I integrate different classifying algorithms in one bagging model?

I use R to do data analysis. I have a dataset. When I use different classifying algorithms, such as random forest, SVM, etc, I have the different accuracy. So, I want to integrate all the algorithms ...