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H: How to do feature selection for classification problem? Which technique will work?
I have 200 variables with 200000 records. How to find best features from this variables? I have tried correlation technique via Heatmap but all the variables have near to same correlation score < 0.4 so it didn't worked.
Please sugge... |
H: Isn't one-hot encoding a waste of information?
I was just playing around with one-hot representations of features and thought of the following:
Say that we're having 4 categories for a given feature (e.g. fruit) {Apple, Orange, Pear, Melon}. In this case the one-hot encoding would yield:
Apple: [1 0 0 0]
Orange: [... |
H: How to deal with multiple categorical data set
Please tell me how with sex, smoker, region?
Should I perform one hot encoder for all?
AI: Simply yes. Before that you may want to check how correlated those features are, so you can simply deselect redundant features, but in general you are right. Starting with one-ho... |
H: What would be a good loss function to penalize big differences and reward small ones, but not in a linear way?
I have an image with the differences between 2 other images. Concentrations of black pixels mean similar regions between the images, whereas, white values highlight differences.
Thus I want a function to ... |
H: Do i need to use hyperparamters from Gridsearch to train on WHOLE training set to get final model?
I just want to make sure i am on the right lines so please correct me if wrong. I am testing which hyperparmets are best for logisitic regession on my data X, y where X is featrues and y is target. X, y are made from ... |
H: Does it make sense to use train_test_split and cross-validation when using GridSearchCV to play with hyperparameters?
I was wondering if my methodology makes sense. I am using GridSearchCV with cross-validation to train and tune model hyperparameters for a bunch of different model types (e.g. Regression Trees, Ridg... |
H: Appending dataframe with .values
Is it necessary to append train X & test X with .values? But I checked and found the model works fine without appending .values, then why append?
In other words.. which among the following is better, and why?
X = df.iloc[:,4].values
OR
X = df.iloc[:,4]
AI: .values coverts the datafr... |
H: Meaning of 'hue" in seaborn
I know what "hue" does a little
I'm studying kaggle and the image is about bike sharing demand analysis
What I want to know is
shouldn't the second images's sum of each point's y axis be the first images's point's y axis??
AI: You would expect that to be the case, however, by default se... |
H: Convert CSV from an api to a dataframe format in python
I am new to python, I have extracted some reviews from a website and I used the api of the webscrapping tool to import my data in python and the format is in csv. I want to convert this csv to a dataframe in python. Can someone guide me on how to perform this... |
H: ROC AUC score is much less than average cross validation score
Using Lending club Dataset to find the propability of default. I am using hyperopt library to fine tune hyper parameter for an XGBclassifier and trying to maximize the ROC AUC score. I am also using Random over sampling inside the pipeline and performin... |
H: Keras BatchNormalization axis
I use spectrogram as input to a Convolutional Neural Network I have created with tensorflow.keras in Python.
Its shape is (time, frequency, 1).
The input's shape of the CNN is (None, time, frequency, n_channels) where n_channels=1 and the first layer is a Conv2D. In between every Con... |
H: order of features for model tuning vs model fitting
Assuming that the same columns (i.e., features) are used for hyperparameter tuning and model fitting, and ensemble models are used for modeling (e.g., Random forest or XGboost), then does the order of columns used during the hyperparameter tuning process should be... |
H: Data science career problems: interaction of technical and social difficulties
I have been trying to break into the bioinformatics space (and now, data science more generally).
Although there are numerous challenges in this field and I am constantly learning to deal with them, I have have found the most consistent ... |
H: LabelEncoder with a Multi-Layer Perceptron?
So we're working on a machine learning project at work and it's the first time I'm working with an actual team on this. I got pretty good results with a model that uses the following SKLearn pipeline:
Data -> LabelEncoder -> MinMaxScaler (between 0-1) -> PCA (I go from 13... |
H: order of features importance after make_column_transformer and pipeline
I have a data preparation and model fitting pipeline that takes a dataframe (X_trn) and uses the ‘make_column_transformer’ and ‘Pipeline’ functions in sklearn to prepare the data and fit XGBRegressor.
The code looks something like this
xgb = X... |
H: predicting next jobtitle
I have a dataset of which has 30M rows each like [current_jobtitles, nextjobtitles].
[['junior software programmer', 'senior software programmer'],
['senior software programmer', 'lead software programmer'],
['sales associate', 'regional sales associate']]
I want to build a deep learning... |
H: Help with algorithm approach for computer vision
I hope this is the right forum to ask.
I had a client approach me with a demand for a vision system for their assembly line.
The problem they are facing is that the operator sometimes forgets to put all three parts of the product together. They want a vision system t... |
H: How is the GridsearchCV Score calculated?
How is the score of GridsearchCV calculated? Is the score a percentage? Does this mean higher is a better?
AI: The score is based on the scorer defined in the scoring argument. Meaning, the scorer can be any of the default metrics, such as precision, accuracy or F1-score
(e... |
H: Data augmentation in deep training
I'm trying to understand the role of data augmentation and how it can affect the performance/accuracy of a deep model. My target application is a fire classification (fire or not, on video frames), with almost 15K positive and negative samples, and I was using the following data a... |
H: EfficientNet: Compound scaling method intuition
I was reading the paper EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks and couldn't get my head around this sentence:
Intuitively, the compound scaling method makes sense because if the input image is bigger, then the network needs more laye... |
H: How to impute right-censored data
I have a dataset of vectors representing movement with various characteristics. Some vectors represents the movement that was stopped by external factor and therefore, observed value for length of such a vector (v_length) is incomplete (marked as incomplete == 1). The data looks l... |
H: what metrics to evaluate rank order results?
I have searched on stackexchange and found a couple of topics like this and this but they are not quite relevant to my problem (or at least I don't know how to make them relevant to my problem).
Anyway, say I have two sets of prediction results, as show by df1 and df2.
y... |
H: What is the name of this statistical interaction?
What is the name of the following statistical / informational interaction:
given A, I know exactly what B is.
given B, I know to some extent what A is.
I'm not looking for a probability but rather something like correlation.
Something that tells me that I don't need... |
H: What are features in computer vision?
I'm learning how U-NET network works to do semantic segmentation.
I think I have understood everything but features. What are those image features?
I read that convolutional layers extract features from the images using their filters, but what are they? Are they corners? edges?... |
H: Class asks me to give self for Naive Bayes Model python
I try to use the following code but when I try to use fit function with my X_train and y_train,
I get the following error:
fit() missing 1 required positional argument: 'self'
I do not know much about classes but I know it should not ask for self. I found so... |
H: Plot dataframe with two columns on the x axis
how would I plot the data below with the x axis as Year & Month? Each Year-month combination has a unique monthly count (Y). I am unsure how to proceed, given than they are in different columns, should I combine them first?
AI: Using matplotlib, you could create a custo... |
H: Does building a corpus make sense on a documentation project?
I have zero to experience in data science or machine learning. Because of this I am not able to determine if building a corpus does apply to the problem I am trying to solve.
I am trying to build a reference site for cloud technologies such as AWS Google... |
H: K-Means Clustering too crowded
I have written a simple python code that opens a csv files and then clusters the values of one column. There around 10k rows
This is my code
import pandas as pd
import numpy as np
import random as rd
import matplotlib.pyplot as plt
data = pd.read_csv('file.csv', encoding='unicode_esc... |
H: How to train my model efficiently?
I am new to ML and have been reading online about training bottlenecks when there are frequent updates to data.
Let's say I have a built a model based on a dataset of 10M records.
Now, in another 2 months, I might receive another 1M records which we would like to feed into our mod... |
H: How to preprocess data for Word2Vec?
I have text data which is crawled from websites. I am preprocessing data to train Word2Vec model. Should I remove stopwords and do lemmatization? How to preprocess data for Word2Vec?
AI: Welcome to the community,
I do not know about other libraries, but gensim has a very good A... |
H: How to calculate the final adjusted weights for a neural network model
My understanding of a neural network algorithm is the 1st row/observation of the dataset is inputted into the NN model and then backpropagation happens to adjust the weights, until some condition is met and the weights stop adjusting. This then ... |
H: How are the channels handled in CNN? Is it independently processed or fused?
Let's assume that we are talking about 2D convolutions applied on images.
In a grayscale image, the data is a matrix of dimensions $w \times h$, where $w$ is the width of the image and $h$ is its height. In a color image, we normally have ... |
H: What is the feedforward network in a transformer trained on?
After reading the 'Attention is all you need' article, I understand the general architecture of a transformer. However, it is unclear to me how the feed forward neural network learns.
What I learned about neural nets is that they learn based on a target ... |
H: Semantic text similarity using BERT
Given two sentences, I want to quantify the degree of similarity between the two text-based on Semantic similarity.
Semantic Textual Similarity (STS) assesses the degree to which two sentences are semantically equivalent to each other.
say my input is of order:
index line1 ... |
H: How do I know the best pruning criteria for decision trees?
Right now,I am working on decision trees on python,how do I know what would be the best pruning criteria based on my data?
AI: Experimentally: using cross-validation on a subset of your training data, compute the performance of every option that you want t... |
H: Slightly different results between scipy.stats.spearmanr and manual calculation
I have the following dataset.
When I calculate the Spearman correlation coefficient with scipy.stats.spearmanr, it returns 0.718182.
import pandas as pd
import numpy as np
from scipy.stats import spearmanr
df = pd.DataFrame(
[
... |
H: ADAM algorithm for multilayer neural network
I’m trying to touch neural networks without using “in box” algorithms. And so I found out that nowhere is written how to calculate square of gradient for hidden layers in ADAM optimizer.
I took the description from original article and the problem is that Vt is some kind... |
H: Correlation based Feature Selection vs Feature Engineering
I'm a bit confused about the superiority of Feature Selection over Feature Engineering or vice versa.
Let's say I just want to get the best possible performance on a couple of models like a neural network, something tree-based and a Naive Bayes Classifier.
... |
H: UniLM - Unified Language Model for summarization
The UniLM claims to be the best approach for summarization task. But there doesn't seem to be any tutorial or how-to section in the README.md or any other blog. How exactly can I use this state-of-the-art library for abstractive summary generation?
Github link
Paper
... |
H: How should I read the following heatmap?
I've been playing around with the linear regression, and I was thought that before commencing it's always good to plot an heatmap to see whether there are features that somehow is worth testing for their significance/relationship.
Would you agree with the above?
With that be... |
H: Multi-class clasification
Just getting my toes wet with running some models on the Iris dataset and was wondering if using One-vs-Rest is required or not? Because I can fit a linear model without it, but using OVR yields different results.
Any explainations would be great, thank you!
AI: Linear regression is not a... |
H: How to predict an outcome within a specific time window?
I have a dataset which has around 10K records.
My objective is to predict whether the customer will churn or not. Binary classification problem with each class representing around 55:45 proportion and 20 features.
I understand when it's just about prediction,... |
H: Classification model using RNN(action detection)
1) Could it be useful to use RNN for classification problem?(e.g.
to distinguish which action is taken: car is going, walking,
digging, nothing).
If 1 question is positive, how should RNN structure look like?
I have dataset of 4 actions, many examples for each acti... |
H: Papers presenting results that are worse than random chance
Is it me or has there been an increasingly large amount of object detection papers describing models that are performing worse than chance. Here is an example (an extract so not to name names):-
AP represents the average precision. No mention of recall... |
H: Using Tensorflow object detection API vs Keras
I am new to machine learning. I am curious to know what is the difference between using Keras instead of TensorFlow object detection API. We need to manually configure hidden layers and input layer in Keras so what is the advantage to use Keras and how to know how many... |
H: Reinforcement Learning: Policy Gradient derivation question
I have been reading this excellent post: https://medium.com/@jonathan_hui/rl-policy-gradients-explained-9b13b688b146 and following the RL-videos by David Silver, and I did not get this thing:
For $\pi_\theta(\tau) = \pi_\theta(s_1, a_1, ..., s_T, a_T) = p(... |
H: Random Forest workflow?
I have a data-set comprised of a fairly large number of columns (over 1000) relative to the number of rows (370) that I am currently running a random forest regression on. I am a little confused with respect to the best way to go around various tasks such as feature selection and cross-valid... |
H: why we need data labelling tool for computer vision?
Before start training images with tensorflow object detection api we need to use labelling tool to annotate our images and converted to XML format.
What happens when we convert our annoted image to XML file? Why we need that?
AI: You need to label data in order t... |
H: What is the “learning” step in Gaussian Naive Bayes classification?
For conditionally independent features $f_i$, Naive Bayes Classification gives me the classifier
$Classifier(f) := \arg \max_{k} P(C=k) · ∏^n_{i=1} P(f_i|C=k)$
for classes $k$. I understand that for Gaussian Naive Bayes, I can assume normally dis... |
H: Performance gain of GPU when learning DNNs
Currently, I learn deep neural networks on my CPU (i7-6700K) using TensorFlow without AVX2 enabled. The networks need about 3 weeks to be learned. Therefore, I am searching for a (cheap) way to speed up this process. Is it better to compile TensorFlow enabling AVX2 or to b... |
H: How to begin understanding of audio and music analysis
I recently have been assigned to do some work with the python libROSA library. I don't have extensive experience with audio and music analysis and the apis and docs seem to assume a higher level of understanding. For example, the hello world example says thin... |
H: Weka: Implementation of Random Forest
I am wondering how random forests are exactly implemented in Weka. This paper is very specific about RFs in Weka, but the description of its learning process in chapter 2 seems strange to me.
They say:
Bootstrap samples $B_i$ for every tree $t_i$
A random subset of features is... |
H: What is "Laplacian image space"?
I have been working through Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis where the authors make the following claim (subjection 2.2.1):
...the Laplacian space is more robust to illumination changes and more ... |
H: Which data set to use to find correlation between Predictor and response variables? Test data set? Training data set? or the entire data set?
I have a dataset with 4 predictor variables X1, X2, X3, X4, and one response variable Y. I have been asked to check the correlation between these variables and see how they a... |
H: Assign a unique cluster based on a dataframe column with KMeans Algorithm
I have the following df
x1 x2 x3 x4
1000 5000 0.8 restaurant1
2000 7000 0.75 restaurant1
500 1000 0.5 restaurant2
700 1400 0.6 restaurant2
1000 5000 0.8 restaurant2
100 6... |
H: Comparing one small dataset with a big dataset for similar records
I create a varying small dataset (dataset: X) with 500 records in each query. Everytime I need to compare the dataset with a bigger one (dataset: A) (15 milion records) to find similar (or semi-silmilar) values from three different columns. The valu... |
H: How to comptute principal component from three points in two dimensional space?
I have the following question:
Given 3 points (-1, 1), (0, 0), (1, 1). What's the first principal component and what are the coordinates of the projected data points? What would be the variance of the projected data? How to reconstruct... |
H: How can you include information not present in an image for neural networks?
I am training a CNN to identify objects in images (one label per image). However, I have additional information about these images that cannot be retrieved by looking at the image itself. In more detail, I'm talking about the physical loca... |
H: Is it possible to deploy a python trained machine learning model (e.g. a .pkl file) in C language?
I would like to train my machine learning using Python and libraries such as tensor flow, keras, and scikit-learn. After trained, I would like to export this trained model to a file, so far I have been using the libra... |
H: No statistical significance but observable trends
I have a general inference question regarding scenarios when results from data are not statistically significant but there appears to be an observable trend.
For example, treatment A and treatment B are applied to 2 independent populations. Using a ttest to analyz... |
H: How to select the best model from validation/training/holdout accuracy score
I have made my own function to log all the attempts at hyperparamter tuning, the following information is gathered from a 10 fold cross validation.
But I am struggling to work out which model is best.
+----+-------------------+------------... |
H: Recall score for each sample in multilabel classification
Does it make sense to calculate the recall for each sample in a multilabel classification problem?
Suppose I have 3 data samples, each having its own true set of labels and predicted set of labels.
I want to see the match between the true set of labels and ... |
H: SVM SVC: Metric for parameter optimization on imbalanced data
I trained a multiclass SVC with RBF kernel on a down-sampled (and therefore balanced) dataset.
Now I want to perform grid search to find best cost and gamma.
What performance metric should I optimize for?
I have a highly imbalanced test set. There might ... |
H: Python how to add a condition to the groupby while calculating the median of a field?
I need to add a new condition to the following line:
train["Age"].fillna(train.groupby("Ticket")["Age"].transform("median"), inplace=True)
Currently, its taking the median of the age based on tickets class.
I need to add to this ... |
H: Cross Validation - Why does more folds increase variation?
Can someone explain why increasing the number of folds in a cross validation increases the variation (or the standard deviation) of the scores in each fold.
I've logged the data below. I'm working on the Titanic dataset and there is around 800 instances. I'... |
H: What is the bleu score of professional human translators?
Machine translation models are usually evaluated using bleu score. I want to get some intuition for this score. What is the bleu score of professional human translator?
I know it depends on the languages, the translator ect. I just want to get the scale.
ed... |
H: getting error while scrapping Amazon using Selenium and bs4
I'm working on a class project using BeautifulSoup and webdriver to scrap
Disposable Diapers on
amazon for the name of the item, price, reviews, rating.
My goal is to have something like this where I will split this info in
different column:
Diapers Si... |
H: Machine Learning Out of test data forecast (XGBoost, ANN)
I see a lot of applications for machine learning techniques applied to time series. Unfortunately almost all kernels with XGBoost or ANN stop short in creating an actual forecast. The achieve a great fit as they have the test data exlcuded.Are there any kern... |
H: pivoting two column in pandas
How can I transfer two column features into pivot table on the following dataset
I have tried the aggfunc function but this fill the value either 0 or 1. I want to transfer the row as cell value.
Here is the dataset
content Users
22 1196
23 1196
23 1216
16 8... |
H: How many times is backprop used in epoch?
As I understand for the algorithms that use gradient descent we have to pass data to the algorithms multiple times so that the optimum is found.
So one epoch means that the forward-backprop (and updating weights with gradient descent) is done only once and in order to find ... |
H: Need an advice on research topic
I am about to choose ML research topic for my master thesis, but i am at a dead end. The problem is, that while reading research papers, i find solutions, but not an open problems.
For now, a came up with such ideas:
Research neural network quantization algorithms - i started to re... |
H: Extracting amount from free text
I want to extract various amounts and tenure of contracts from different contract documents that we have.
For example: Mr xyz, this contact is valid for 3 Months and you have to pay $3000 as agreement fee.
Expected output : 3 Months, $3000
Please note that this is just an example bu... |
H: Categorical feature as output and perform a classification
I have a database in which the output feature Y is categorical, for example (oversimplification)
A B C Y
1.0 0.2 5.1 Car
3.0 1.1 0.1 Car
7.6 6.9 2.7 Bike
2.5 3.8 0.3 ... |
H: Closed form of Weighted Ordinary Least Squares calculation of the trend line
I would like to know if there is a closed form version of this equation:
$\beta = \frac{n\sum{xy}-\sum{x}\sum{y}}{n\sum{x^2}-(\sum{x})^2}$
But for weighted data, where the weight $w_i$ is the value of the importance I want the individual $... |
H: Processing data in the right manner in data science
From what i have learned, people say that it is more correct if i preprocess data after splitting it to train/test dataset. My questions are
1.Does it mean we detect flaws of the data + preprocess it after the splitting? if yes/no, why?
2.Is it okay if i detect fl... |
H: Bayesian regularization vs dropout for basic ann
Does it make sense conceptually to apply dropout to an artificial neutral network while also applying bayesian regularization?
On one hand I would think that technically this should work just fine, but on the other hand if bayesian regularization is like finding the ... |
H: Reshaping Pandas DataFrame
I am trying to do the following as shown below.
Input Output
Letter Number A B C
A 1 1 1 1
A 2 2 2 2
B 1 3 3
B 2 4
B 3
C 1
C 2
C 3
C 4
I have wrote the following code which works just fine.... |
H: I have a pandas dataframe and i need to clear all the special characters other than space
Input:
import pandas as pd
df=pd.read_excel("OCRFinal.xlsx")
df['OCR_Text']=df['OCR_Text'].str.replace(r'\W+'," ")
print(df['OCR_Text'])
Output:
The excel removes all the special characters along with the space. But i dont w... |
H: Interpretable xgboost - Calculate cover feature importance
When trying to interpret the results of a gradient boosting (or any decision tree) one can plot the feature importance.
There are same parameters in the xgb api such as: weight, gain, cover, total_gain and total_cover. I am not quite getting cover.
”cover... |
H: XGBOOST - different result between train_test_split and manually splitting
I am trying to train XGBOOST model.
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=43, stratify=y)
when I'm using train_test_split and pass the model X_train, Y_train and for eval_set X_test, Y_test, T... |
H: AUC ROC metric on a Kaggle competition
I am trying to learn data modeling by working on a dataset from Kaggle competition. As the competition was closed 2 years back, I am asking my question here. The competition uses AUC-ROC as the evaluation metric. This is a classification problem with 5 labels. I am modeling it... |
H: Simple Imputer cannot impute by column
I have X_train that shapes (14599, 13), i'm trying to impute NaN with column's median but somehow it imputes with row resulting error because in a row there are date, and other than integer values. I already lookup if SimpleImputer has axis parameter but could not find that it... |
H: How to use Keras predict_generator() for segmentation output?
Below is the code I'm using for segmentation mask prediction after using fit_generator(...) on model named m :-
test_datagen = ImageDataGenerator(rescale=1./255)
test_generator.reset()
test_generator =test_datagen.flow_from_directory('result/test', c... |
H: Purpose of validation data NN
Aside from using validation data to tune the hyperparameters is there any other benefit to including validation data to the model?
All I ever read about is it being used to tune hyperparameters and check for overfitting. Is the checking for overfitting separate from tuning the hyperpar... |
H: How can I provide an answer to Neural Network skeptics?
After given several talks on NN's, I always have a skeptic that wants a real measure of how well the model is. How do you know the model is truly accurate?
I explain the use of test data etc. to evaluate the total error, however, there is always someone who wa... |
H: searching for clouds (in the sky) images big dataset
I'm looking for a big dataset of clouds (in the sky) ground based images. i need tens of thousands of images.
It is important that the images will be ground based and not from satellite/ flights.
I've tried to search and so far found datasets of hundreds/thousan... |
H: Different results obtained for OneVsOneClassifier (or OneVsRestClassifier) when using ordinary KFold and StratifiedKFold cross validation
When I fitted a OneVsOneClassifier (or OneVsRestClassifier), I noticed I obtained different results when I used ordinary KFold and StratifiedKFold cross validation. The testing s... |
H: Understanding Terminology in Goodfellow's paper on GANS
I am trying to understand Ian Goodfellow et al's paper Generative Adversarial Nets here.
In section 3 the author's write:
The adversarial modeling framework is most straightforward to apply
when the models are both multilayer perceptrons. To learn the
ge... |
H: Does k fold cross validation become less useful when number of observations is very large?
As seen in the accepted answer for variance of k-fold cross validation ,
the simulation shows that k-fold CV has the same test error rate for different values of k when n=200.
Does this mean that k-fold validation is likely t... |
H: Scikit-learn OneHotEncoder effect on feature selection
If I need to run feature selection on my dataset isn't it problematic to use OneHotEncoder? Couldn't it then decide to remove a one of the encoding columns? How should I deal with this? Thank you.
AI: Yes it would be possible that it happens. It means that this... |
H: How to adaptively sample n-dimensional data and build an optimum training set
My input space is at least 10 dimensional (after reducing it by various component analysis such as PCA) and the output space is 4 dimensional. I am building a neural network that works something like a function approximator which takes th... |
H: Error in numpy array assignment
I'm trying to upload 17 images into a 4d numpy array, each image size is (256,256,1), so basically I'm using the 0th dimension for collection of different images. Following is my code:
import numpy as np
test_ip=np.zeros(shape=(17, 256, 256, 1))
count=0
for img in image_generator1:
... |
H: What is done first, cross validation or grid search?
When I have the data set to train a model with SVM, which procedure is performed first, cross validation or grid search? I have read this in a couple of books but I don't know in what order all this should be done. If cross-validation is first performed, what hyp... |
H: Rendered Image Denoising
I am learning about "Image Denoising using Autoencoders". So, now I want to build and train a model. Hence, when I read into how Nvidia generated the dataset, I came across: We used about 1000 different scenes and created a series of 16 progressive images for each scene. To train the denois... |
H: How can I find to starting point of skewed data in python?
I have a list like this,
import random
import seaborn as sns
years = []
for i in range(1000):
if i % 100 == 0:
val = random.randint(1900, 2000)
else:
val = random.randint(2000, 2021)
years.append(val)
sns.distplot(years);
He... |
H: how to create a searchable tree on Persian text?
I wanna clean my huge text data from stop-words. I already have stop-word data that is provided on the below link. It seems to me, if I have a pre-built tree on stop-words, I could save lots of time. I want to search each word of text in this pre-built tree, if the w... |
H: What does the number after a machine learning model name mean?
I'm not sure if this is off-topic, but I'm posting here anyway.
So I saw lots of machine learning models have like an ID after their names, for example, resnet101, resnet152, densenet201 etc. What exactly do those numbers 101, 152 and 201 mean? And how ... |
H: (Basic) statistics
I got a misunderstanding regarding basic statistics (I think) but I can't get my head around that:
I did an online survey regarding the usage of some application. The user could answer 1 (I don't know that application), 2 (I know that) or 3 (I use that).
Now I want to know, how many applications ... |
H: Does it make sense to use a tfidf matrix for a model which expects to see new text?
I'm training a model to classify tweets right now. Most of the text classification examples I have seen convert the tweets into tf-idf document term matrices as input for the model. However, this model should be able to identify new... |
H: Why are the weights of my first layer and last layer in the CNN change while the middle layers don't?
The weights of my first and last convolution layers do change in a noticeable way. However, the rest of my convolution layers, in the middle, do not.
I should add that all convolution layers' biases change noticeab... |
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