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H: How to use two different datasets as train and test sets?
Recently I started reading more about NLP and following tutorials in Python in order to learn more about the subject. The problem that I've encountered, now that I'm trying to make my own classification algorithm (the text sends a positive/negative message) ... |
H: Can we remove features that have zero-correlation with the target/label?
So I draw a pairplot/heatmap from the feature correlations of a dataset and see a set of features that bears Zero-correlations both with:
every other feature and
also with the target/label
.Reference code snippet in python is below:
corr ... |
H: How can I calculate AUC from the ROC curve for the classification?
Based TPR and FPR, I have generate ROC curve for my binary classification model. I do not know, how to calculate AUC value. I would be very help for me if you can help me to calculate AUC value.
AI: Welcome to the community!
As you know, AUC is just... |
H: Standardizing Vegas odds for a randomForest
I'm sorry I don't have reproducible code, but I have a pretty specific question that I can't find an answer to.
I'm using randomForest to project NBA statistics. Vegas-odds are incredibly useful because it's provides the wisdom of the crowd. Intuitively I feel like they ... |
H: Meaning of stratify parameter
I'm training a Neural Network and I'm trying to divide my data into training and testing sets. I have a lot of output classes and for some of them I have as little as 2 examples, so I would like to have, in that case, 1 example in training and 1 example in testing. From what I've read,... |
H: Extracting Useful features from large convolutional layers
I have been training a convolutional neural network on emotion detection. Now, I would like to extract features for my data to train an LSTM layer. In my case, the top convolutional layers in the network has the following dimensions: [None, 4, 4, 512] and [... |
H: Why my model can't recognise my own hand written digit?
Currently i am working on digit recognizer[0-9]. My model train accuracy 100% and test accuracy 90%. But when i train to feed my own written digit, it always give me wrong prediction.
I know test and train images should come from same source. But how could i... |
H: Sentimental Analysis on Twitter Data
What are best ways to perform sentimental analysis on Twitter Data which I dont have labels for?
AI: You should look at literature on unsupervised sentiment analysis. The paper by Peter Turney could be a good starting point.
Thumbs Up or Thumbs Down? Semantic Orientation Applied... |
H: How does combining neurons create non-linear boundaries?
I have been working with NNs for a while, but haven't dug too deep into this unfortunately.
By looking at the three neurons below, in each of their boxes we can see that they are really just making linear separations in the x1, x2 plane (of course not taking... |
H: What Base Should Be Used For Negative Log Likelihood?
When calculating the negative log likelihood loss, what base of log are we supposed to use?
AI: Typically it is implemented as the natural logarithm, base e. Other bases can be used for the same effect though. |
H: neural network training algorithms
When I first read about neural networks, I learned that Backpropagation is the algorithm used to train the neural network. I am interested if there are other alternatives (or better?) to BP.
What are the other training algorithms used in NN? And is BP is the best one, and that's ... |
H: Transformation of categorical variables (binary vs numerical)
When using categorical encoding, I see some authors use arbitrary numerical transformation while others use binary transformation. For example, if I have a feature vector with values A, B and c. The first method will transom A,B and C to numeric values ... |
H: What is the advantage of using log softmax instead of softmax?
Are there any advantages to using log softmax over softmax? What are the reasons to choose one over the other?
AI: There are a number of advantages of using log softmax over softmax including practical reasons like improved numerical performance and gra... |
H: Replacing column values in pandas with specific column with multiple database operation?
Need to replace database of the column in specific refine query with multiple operations as mention in below image. Trying such operation as an individual, but can't understand which method to use can make in one column with mu... |
H: Twitter Retweet Network Visualization
I am trying to visualize retweet network in order to find out which users are most likely to have most influence on other users. Here is my code:
import networkx as nx
G_retweet = nx.from_pandas_edgelist(translated_iranian_tweets,
... |
H: Why can distributed deep learning provide higher accuracy (lower error) than non-distributed one with the following cases?
Based on some papers which I read, distributed deep learning can provide faster training time. In addition, it also provides better accuracy or lower prediction error. What are the reasons?
Que... |
H: Train a deep reinforcement learning model using two computers
I would like to know if there is a way to train a deep rl model using two different computers. The first one would execute the game and send requisitions to the second computer which would store and train the model itself.
Obs: The computers aren't in t... |
H: Non-prediction Applications of Machine learning
Prediction seems to be the dominant theme of machine learning. Most algorithms have fit and predict functions so that model can be created which can predict outcomes or other parameters of interest from new set of features.
What are non-prediction applications of mac... |
H: not quite sure about the difference between RNN and feed forward neural net
I'm a bit confused after reading this paper: https://arxiv.org/abs/1705.09851
on page 22, the author writes
response:
\begin{equation}
Y = softmax(Z^{L-1})
\end{equation}
and hidden state
\begin{equation}
Z^\ell = max(W^\ell *Z^{\ell-1} + b... |
H: What could be a dataset in which the presence of an outlier dramatically affects the performance of Ordinary Least Squares (OLS) regression?
I am tasked with giving an example of a dataset in which the presence of an outlier dramatically affects the performance of
Ordinary Least Squares (OLS) regression. I've searc... |
H: How do I use a custom stopwords filter in the Java Weka API?
I am using the Java Weka API to build a classification model. I can use the builtin stopwords filter. However, I need to use a custom filter for my problem. I do not know how to use a custom stopwords filter in the Java Weka API.
AI: You can try the follo... |
H: How can I use Machine learning for inter-relationship between Features?
Machine learning is used mostly for prediction and there are numerous algorithms and packages for this.
How can I use machine learning for studying inter-relationships between features? What are major packages and functions for this? Are there ... |
H: How to use SMOTE in Java Weka API?
I am trying to build classification model using Java Weka API. My training dataset have class imbalance problems. For this reason, I want to use SMOTE to reduce class imbalance problem. But, I do not know how to use it in Java Weka API.
AI: Welcome to the community.
You can use t... |
H: How to calculate TPR and FPR for different threshold values for classification model?
I have built a classification model to predict binary class. I can calculate precision, recall, and F1-Score. Now, I want to generate ROC for better understanding the classification performance of my classification model. I do not... |
H: does xgb multi-class require one-hot encoding?
I was trying an xgboost from python with a multiclass single-label problem and assumed the label can be an integer indicating my class (as opposed to eg one-hot) .
params = {'eta': 0.1,
# 'objective': 'binary:logistic',
'objective': 'multi:softmax'... |
H: Wilcoxon W value different from python
I use data from https://en.wikipedia.org/wiki/Wilcoxon_signed-rank_test, W value is 9.
But, for the following code W value is 18,
what is the reason?
# Wilcoxon signed-rank test
from numpy.random import seed
from numpy.random import randn
from scipy.stats import wilcoxon
# see... |
H: Should the minimum value of a cost (loss) function be equal to zero?
We know optimization techniques search in the space of all
the possible parameters for a parameter set that minimizes the cost function of the model. The most well-known loss functions, like MSE or Categorical Cross Entropy, has a global minimum v... |
H: sales price prediction
I have to find make a classifier for price prediction of a item. The question I have is which columns I should choose for price prediction.
Also which machine learning classifier would be good to perform this, at present I choose random forest.
Do I need to use time series concept in here?, ... |
H: Exceptionally high accuracy with Random Forest, is it possible?
I need your help to find a flaw in my model, since it's accuracy (95%) is not realistic.
I'm working on a classification problem using Randomforest, with around 2500 positive case and 15000 negative ones, 75 independent variables. Here's the core of m... |
H: What is the classification accuracy of a random classifier?
I have a build a classification model using machine learning technique (SVM). I want to compare the classification accuracy of my model with a random classifier. My data set contains only two classes(1 or 0). The ratio of 1 and 0 instances are 35% and 65%.... |
H: TD Learning formula
This is something I cannot get my head around and initially I thought is a typo but it is not.
Essentially in TD learning, we are trying to learn the Value Function. A value function tells me how favourable a state/observation is. Assuming ~~~discount/decay/lambda~~~ factor of 1, if V(s) is 10 ... |
H: Is the ultimate challenge in ML simply computational power?
I am stuck on a theoretical roadblock in learning about machine learning, because I have not seen this explicitly addressed anywhere. In my studies, it seems as if Cross-validation (or some variant thereof, like LOOCV, or potentially another, but similar, ... |
H: why nobody uses matlab
I wonder why most people now don't use matlab. I guess the reason is matlab is not free, so companies don't want to use it, then interviewees don't use it, then schools don't encourage it, then nobody ends up using it.
But I like it, compared to C++, Python, for it's convenient to plot figure... |
H: What's the difference between Sklearn F1 score 'micro' and 'weighted' for a multi class classification problem?
I have a multi-class classification problem with class imbalance. I searched for the best metric to evaluate my model. Scikit-learn has multiple ways of calculating the F1 score. I would like to understan... |
H: Is there any way how to make samples balanced?
I have a dataset which consists of attributes on breakdown of machines.The target variable is machine status which are populated with ones and zeros. The distribution of ones and zeros are given below
0 - 19628
1 - 225
0 - signifies the machine is running good and 1... |
H: Why is sklearn.metrics.roc_auc_score() seemingly able to accept scores on any scale?
I had input some prediction scores from a learner into the roc_auc_score() function in sklearn. I wasn't sure if I had applied a sigmoid to turn the predictions into probabilities, so I looked at the AUC score before and after appl... |
H: Does discretization of continuous features also lose information about distance?
During discretization, it "squashes" nearby values into one bin, losing a little bit of information along the way.
But doesn't it also lose information about distances of features? For example, if we have height as continuous feature, ... |
H: How to model & predict user activity/presence time in a website
I need to make a prediction model based on some historical data from a website's user login system. Suppose my dataset has some features like user login time and logout time for each day for a specific user. Login and logout times can be multiple in a ... |
H: NEAT XOR Example gives different results at each run
I have just started learn to use NEAT algorithm. I was thinking I understood the basics of NEAT when I read "Evolving Neural Networks through
Augmenting Topologies" paper and current python documentation. However, in practice I m in trouble.
I have run XOR examp... |
H: What is the the cost of combining categorical variables?
I have 2 categorical variables e.g. state and city. Missing are only in city. As opposed to throwing out all observations with missing values for city or throwing out city all together I was considering making a variable location that is a concat of the two c... |
H: Logistic regression cost function
In Aurelien Geron's book I found this line
This cost function makes sense because –log(t) grows very large when t approaches
0, so the cost will be large if the model estimates a probability close to 0 for a positive instance, and it will also be very large if the model estimates... |
H: help with Keras sequential model output
I have trained a sequential model with keras for MNIST dataset and this is the code I've used.
# Create the model
model = Sequential()
# Add the first hidden layer
model.add(Dense(50, activation='relu', input_shape = (X.shape[1],)))
# Add the second hidden layer
model.add(D... |
H: normalization of probabilities in predicting a poly-neuron output in neural nets
When predicting a poly-neuron output in neural nets, say, predicting multiple handwritten digits and giving an output neuron vector (0.1,...,0.9,0.1,...), many use sth like softmax (or sth like the energy dependent probability exponent... |
H: How to fill missing numeric if any value in a subset is missing, all other columns with the same subset are missing
There is a clear pattern that show for two separate subsets (set of columns); If one value is missing in a column, values of other columns in the same subset are missing for any row.
Here is a visual... |
H: Higher dimension data visualization in Matlab/Octave
I am working on sparse recovery for a classification task. I use Pine hyperspectral dataset which is a freely available dataset and this image contains 200 Dimension (Depth/channels/bands). In addition, this dataset contains labels (Ground truth information). Thu... |
H: How to sort list by parameter in python?
I have a list of employee records. Each tuple of the list represent a person's record, which includes his name, ID, and age.
For example,
emp_records = [('Karim',100, 45), ('Rahim',10, 30),('Salim', 300,60),('Abu',50,35)]
Now, I want to sort emp_records based on ID.
AI: Yo... |
H: How to sort two dimensional array in Java?
I have a two dimensional double array. I need to sort my based column 1 in descending order. How can I sort my two dimensional array in descending order.
Sample data and code are the following:
package mypro.com;
public class SortDoubleArrary {
public static void... |
H: For text classification that has innumerable features, how do I choose the number of neurons and layers for MLPClassifier?
In my use case of text classification (identify the author from a subset of 10 authors), I find that post all processing with trigrams, there are a 100 thousand and odd features with nearly 50k... |
H: Free Service for Alpha Zero training
I'm an AI student I need to train a deep neural network using the Alpha Zero (Silver et al) for a simple game using this implementation: http://web.stanford.edu/~surag/posts/alphazero.html. I was wondering if any cloud provider like Google or Amazon offers a free trial which suf... |
H: Classification vs Regression Algorithms - Should exists algorithms only for Classification and/or Regression
Dummy question:
There exists algorithms that should only be used for Classification or Regression problems?
For example, should Random Forest should only be apply on Classification problems and Neural Netwo... |
H: YOLO layers size
According to the original paper, the input size of the YOLO network layer is 448x448x3 and after the filter (7x7x64-s-2) is applied the output shape is to be 221x221x192 as I suppose. Some sources assert that the output shape is 224x224x192 but how is it possible if we don't use the kernel (2x2x64-... |
H: YOLO pretraining
I'm implementing YOLO network and have some questions. In the original paper the authors say: "For pretraining we use
the first 20 convolutional layers from Figure 3 followed by a
average-pooling layer and a fully connected layer". And also they report that they use ImageNet 1000 classes dataset an... |
H: Does image resizing lower the prediction accuracy of MLP?
I am implementing a vanilla neural network (MLP) to do image classification in python using tensorflow on images of honey bees to detect their health status. The images in my dataset are of different shapes and sizes, so I decided to do image resize using cv... |
H: Outputs of an LSTM Cell
from each cell of lstm, what are the output's and what does they signify? i understand that there will be three outputs. A long term memory, short term memory and a output. But, i am little confused from colah blog which can be found here. Here he shows that there will be three outputs, one ... |
H: Does policy optimization learn policies to make better actions with higher probability?
When I talk about policy optimization, it is referred to the following picture, and it is linked to DFO/Evolution plus Policy Gradients.
I would like to know is it correct to say: Policy Optimization learns policies to make b... |
H: How can I augment my image data?
What are the correct and common ways to normalize image for CNN?
I used to work with text and it was pretty straightforward. Removing stop words, clean text from noise, tokenization, stemming etc. There is no problem with length we can easly add padding. I am not sure how to treat i... |
H: What does the embedding mean in the FaceNet?
I am reading the paper about FaceNet but I can't get what does the embedding mean in this paper? Is it a hidden layer of the deep CNN?
P.S. English isn't my native language.
AI: Assume you have features wich lie in a $R^n$ space, e.g. your input is a picture with $28 \ti... |
H: Do we need to add the sigmoid derivative term in the final layer's error value?
I have been studying professor Andrew Ng's Machine Learning course on Coursera. Currently, I am trying to prove the formulas for backpropagation, which is mentioned in Week 5 (in this document). Clearly, it mentions that
δ(L) = a(L) − ... |
H: Why would a fake feature with random numbers get selected in feature importance?
I'm using a sklearn.ensemble.RandomForestClassifier(n_estimators=100) to work on this challenge:
https://kaggle.com/c/two-sigma-financial-news
I've plotted my feature importance:
I created a fake feature called random which is just nu... |
H: What kind of "vector" is a feature vector in machine learning?
I'm having trouble understanding the use of Vector in machine learning to represent a group of features.
If one looks up the definition of a Vector, then, according to wikipedia, a Vector is an entity with a magnitude and direction.
This can be understo... |
H: Does fine-tuning of transferred layers perform better than frozen transferred layers?
I recently learned concepts of transfer learning. Is it necessarily true that fine-tuning of transferred layers perform better than frozen transferred layer? why?
AI: Transfer learning means to apply the knowledge that some machin... |
H: Branch of data science that covers event based time series?
Let's say I have discrete events in time, e.g. patients getting sick, and I want to predict whether theses events are indicators of some other underlying event, e.g. a disease outbreak. Usually, one would transform the event based time series into a regula... |
H: Understanding Exclusive-OR predictions in Elman network
I have been reading Elman network paper, which can be found Here. in page 185, under Exclusive-OR section it was written as follows.
Notice that, given the temporal structure of this sequence, it is only sometimes
possible to predict the next item correctly... |
H: How to include class features to linear SVM
I am planning to do a simple classification with a linear SVM. One feature I have is another classification of some sort done previously.
Can I just use this class feature as a 1-hot encoded array? So, e.g. for 3 different classes, I'd have 3 binary features being 0 or 1?... |
H: How to use a NN architecture that is too big for GPU?
Initially posted in Stack Overflow.
I would like to implement a model which is actually 2 neural networks stacked together. However the size of these 2 architecture is too big to fit in GPU at the same time.
My idea was the following :
Load the first model and ... |
H: What is meant by Distributed for a gradient boosting library?
I am checking out XGBoost documentation and it's stated that XGBoost is an optimized distributed gradient boosting library.
What is meant by distributed?
Have a nice day
AI: It means that it can be run on a distributed system (i.e. on multiple networked... |
H: Why isn't my model learning?
import numpy as np
from keras.datasets import cifar10
from keras.layers import Dense, Activation
from keras.optimizers import SGD
from keras.utils import np_utils
from keras import backend as k
from keras.models import Sequential
(Xtr,Ytr),(Xte,Yte)=cifar10.load_data()
Xtr = Xtr.astyp... |
H: Multiple formulas for r squared eval metric for regression
I was came across different formulas for R squared on different articles.
R Squared = 1 - RSS/TSS
R Squared = ESS/TSS
RSS -Residual sum of squares.
TSS - Total sum of squares.
ESS - Explained sum of squares.
Can any one explain which one should be the cor... |
H: Pandas: How can I merge two dataframes?
I found (How do I merge two data frames in Python Pandas?), but do not get the expected result.
I have these two CSV files:
# f1.csv
num ano
76971 1975
76969 1975
76968 1975
76966 1975
76964 1975
76963 1975
76960 1975
and
# f2.csv
num ano dou url
76971 1975 p1... |
H: prediction for a linear sum
I am learning about SVMs in particular linear SVMs through many questions here. However, one problem i faced is that there seems to be no indepth explanation on how does linear SVM works in terms of predicting new data.
I understand that the main purpose of SVM is to find linear separati... |
H: Does this type of classification exist?
Im fairly new to data science and trying to see if a type of classification exists for my needs.
I understand that a classification into 2 categories will look something like this:
You have 2 desired outcomes and you try to build a model that classifies as 0 or 1. If these m... |
H: The mix of leaky Relu at the first layers of CNN along with conventional Relu for object detection
First of all, I know the usage of leaky RELUs and some other relevant leaky activation functions as well. However I have seen in a lot of papers on object detection tasks (e.g YOLO) to use this type of activators only... |
H: How to apply Stacking cross validation for time-series data?
Normally stacking algorithm uses K-fold cross validation technique to predict oof validation that used for level 2 prediction.
In case of time-series data (say stock movement prediction), K-fold cross validation can't be used and time-series validation (... |
H: Building Stacking machine learning model using three base classifiers
I did a stacking using three base classifiers RF, NB, KN N and metamodel random forest or SVM using sklearn library
But which is strange each time i change the metamodel i got the same results. Is it normal ?????
AI: No, in generally speaking, ev... |
H: How to find the count of consecutive same string values in a pandas dataframe?
Assume that we have the following pandas dataframe:
df = pd.DataFrame({'col1':['A>G','C>T','C>T','G>T','C>T', 'A>G','A>G','A>G'],'col2':['TCT','ACA','TCA','TCA','GCT', 'ACT','CTG','ATG'], 'start':[1000,2000,3000,4000,5000,6000,10000,2000... |
H: Which regularization in convolution layers (conv2D)
I am using Keras for a project. I would like to know if it makes any sense to add any kind of regularization components such as kernel, bias or activity regularization in convolutional layers i.e Conv2D in Keras.
If yes, then which regularization is most useful f... |
H: How max_features parameter works in DecisionTreeClassifier?
What is the parameter max_features in DecisionTreeClassifier responsible for?
I thought it defines the number of features the tree uses to generate its nodes. But in spite of the different values of this parameter (n = 1 and 2), my tree employs both featur... |
H: Why xgboost can not deal with this simple sentence case?
There is only 1 feature dim. But the result is unreasonable. The code and data is below. The purpose of the code is to judge whether the two sentences are the same.
In fact, the final input to the model is: feature is [1] with label 1, and feature is [0] with... |
H: When using Data augmentation is it ok to validate only with the original images?
I'm working on a multi-classification deep learning algorithm and I was getting big over-fitting:
My model is supposed to classify sunglasses on 17 different brands, but I only had around 400 images from each brand so I created a fold... |
H: Tagging documents for doc2vec
I am working on resume parsing script. I am trying to tag documents sentences with TaggedDocument function, provided by gensim.
What I have managed for now is to divide every text into sentence, put into one flat array and give every sentence an i (its order, basically) tag.
tagged_d... |
H: How to rename columns that have the same name?
I would like to rename the column names, but the Data Frame contains similar column names. How do I rename them?
df.columns
Output:
Index([ 'Goods',
'Durable goods','Services','Exports', 'Goods', 'Services', 'Imports', 'Goods', 'Services']
Here, there are thre... |
H: Confused about false positive and false negative in confusion matrix?
I am working on binary classification for classifying cancer=1 and no-cancer=0, I use confusion matrix from sklearn, this is my confusion matrix on test set:
# confusion matrix
[[18 0]
[ 7 15]]
# in my reading the order is:
TN=18
FP=0... |
H: How to calculate $\phi_{i,j}$ in VGG19 network?
In the paper Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network by Christian Ledig et al., the distance between images (used in the loss function) is calculated from feature maps $\phi_{i,j}$ extracted from the VGG19 network,
where $\... |
H: Subsequent convolution layers
Note: I've read How do subsequent convolution layers work? a few times, but it's still difficult to understand because of the parameters $k_1$, $k_2$, and many proposals (1, 2.1, 2.2) in the question. This seems to be complex for other people too, I think I'm not the only one (see a fe... |
H: Loss is bad, but accuracy increases?
I have a multicategorial classification problem for images. There are 5 (imbalanced) classes for which i use different class weights. In general there are only a few training images per class: ~56-238
To classify them, I use a neural network with much data augmentation. I have a... |
H: Capture pattern in python
I would like to capture the following pattern using python
anyprefix-emp-<employee id>_id-<designation id>_sc-<scale id>
Example data
strings = ["humanresourc-emp-001_id-01_sc-01","itoperation-emp-002_id-02_sc-12","Generalsection-emp-003_id-03_sc-10"]
Expected Output:
[('emp-001', 'id-... |
H: Do anomalous input features to autoencoder result in high errors on the corresponding output features?
An autoencoder is trained by replicating each training instance to both input and output. However, when predicting for anomaly detection, will the output error be local to the same output feature(s) that were anom... |
H: Is there an oriented clustering algorithm?
I'm looking for a clustering algorithm that will make cluster depending on a orientation. The DBSCAN algorithm cluster points based on a constant radius :
https://upload.wikimedia.org/wikipedia/commons/thumb/a/af/DBSCAN-Illustration.svg/800px-DBSCAN-Illustration.svg.png
Is... |
H: Training and Test set
I was asked by my supervisor to replicate a result from a former graduate student. My supervisor believes the result of that paper is not accurate and he asked me to find out why! The paper was about conducting a random forest classifier to classify some sort of diseases. I was reading through... |
H: Difference between sklearn’s “log_loss” and “LogisticRegression”?
I am a newbie currently learning data science from scratch and I have a rather stupid question to ask. I’m currently learning about binary classification, and I understand that the logistic function is a useful tool for this. I looked up the document... |
H: How can I create a pixel labelled image for Semantic Segmentation?
I am following the Semantic Segmentation Examples tutorial by MathWorks.
I understand that I can load pixel labeled images
pxDir = fullfile(dataDir,'buildingPixelLabels');
Define the class names.
classNames = ["sky" "grass" "building" "sidewalk"];
... |
H: Convolutional neural networks for non-image applications?
If I remember correctly, Convolutional neural networks (CNN) have first been developed for image classification purposes (see work from LeCun et al.).
The convolution process that "slides" over the input image is helpful indeed to detect some features.
Quest... |
H: How does KNN work if there are duplicates?
I am currently debating with my friend about how KNN handles duplicates. Suppose K = 2, and we have a 1-dimensional set of data points to illustrate my dilemma
I = {1, 2, 2, 2, 2, 2, 6}
Thus is it correct to say that the K=2 nearest neighbours of data point 1 is simply {2... |
H: What is the difference between SVM and logistic regression?
While reading the book by Aurelien Geron, I noticed that both logistic regression and SVM predict classes in exactly the same way, so I suspect there must be something that I am missing. In the Logistic regression chapter we can read:
$σ(t) < 0.5$ when $t... |
H: Pandas DataFrame: Aggregating multi-level groups by matching keys
I have some data that looks like this;
data.head()
stock date binNum volume
0 stock0 d120 2 249500.0
1 stock0 d120 3 81500.0
2 stock0 d120 4 79000.0
3 stock0 d120 5 244000.0
4 stock0 d120 6 175... |
H: why do we have to calculate the entropy of parent node in Information Gain?
Why do we need the entropy of parent node in the Information Gain.
Information Gain = entropy(parent) - w * entropy(children)
We can compare the entropy of the children without the need for the parent entropy.
AI: It's essential; you're com... |
H: Training images with multiple channels
So I have a set of images with 16 layers each.
Is there a good reason to split the channels in a format like
example : [images_length,16,image_width , image_height]
instead of creating something more simple like
example 2 : [images_length,1,image_width * 16 , image_height]
... |
H: Handle 50,000 classes in OneVsRestClassifier
I'm new to data science and NLP. I'm trying to solve a problem that is having 1 million rows and some 50,000 distinct classes. The dataset has some text column as a predictor and the other one is the multilabel responses. I have been using tfidf to represent the text fie... |
H: LSTM - divide gradients by number of timesteps IMMEDIATELY or in the end?
From this answer I know that
the gradient of an average of many functions, is equal to the average of the gradients of those functions taken separately.
The error gradient that you want to calculate for gradient descent is $\nabla_{\theta} C... |
H: Choice of ML algorithm for problem
Working on a school project where we have to match some users based on common interests. Assuming I have a list of inputs like this:
Name Interest1 Interest2 Interest3 Interest4 Interest5
Name Interest4 Interest6 Interest7 Interest8 Interest9
Name Interest1 Interest2 Interest4 In... |
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