Questions tagged [classifier]
The classifier tag has no usage guidance.
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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 ...
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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 ...
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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.
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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 ...
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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 ...
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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?
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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 ...
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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 ...
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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 ...
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68
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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
...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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?
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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 ...
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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 ...
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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 ...
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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. ...
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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 ...
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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:
...
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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_{...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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-...
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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 ...
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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, ...
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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 ...
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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 ...
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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:
...
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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?
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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 ...