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H: Does image's background matter for detector training (CNN)? Does an image's background matter for detector/localisation in the training part (using CNN)? For example, if I want to make a face detector, which one is better as training dataset? Faces cropped dataset Faces in a global scene dataset Does it matter? A...
H: How to implement a Restricted Boltzmann Machine manually? I am learning about Restricted Boltzmann Machines and I'm so excited by the ability it gives us for unsupervised learning. The problem is that I do not know how to implement it using one of the programming languages I know without using libraries. I want to ...
H: GAN for inpainting an image Is it possible to train a GAN model to inpaint an image taken from a specific setting(e.g. an office, woods, beach ...) after we have cropped out people of it? For example, I used this repo's pretrained GAN model on Places2 I used a MaskRCNN model to segment people, and then cropped them...
H: Extract datatable column by indexing a character vector I am asking a similar question to this one except I am trying to index a vector of column names. If I have a data.table like a: a <- data.table("NAME" = c("A", "B", "A"), "PASS_FAIL" = c("F", "P", "P"), "TEST_COUNT" = c(NA, NA...
H: Why is patsy used to prepare data for logistic regression? I'm pretty new to both ML & scikit-learn. I've noticed that some example tutorials & codes online use patsy's dmatrices to prepare data for logistic regression. I don't understand why this is done. Example In the case above for instance, isn't it sufficient...
H: Poor performance of SVM after training for rare events I found out that Weighted SVM is a classification approach to handle class imbalance problem. My data set is highly imbalanced with rare event (minority class, labeled as 1) and the majority class (label 0). So I implemented the supervised classification weight...
H: What is the role of the bias? When talking about artificial neurons, inputs, weights and biases, I understand the role of each but the latter. In short if we have a neuron such as sigmoid(sum(w*x) + b) I get that the weights basically say which of the inputs is more "important", but what about the bias? I've read...
H: Low number of inputs compared to outputs (per row) in neural network I have data that one row has input of size 1x2 (two values) and output is matrix of size 15x3 (fifteen rows with three values) like that |-----------------| |y01,2 y01,2 y01,3| |y02,1 y02,2 y02,3| |....
H: What is meant by 'training patch size'? Currently I read a paper about symmetric skip connections for autoencoder (link). One experiment of them changes the the 'training patch size'. In my understanding patches are sub-boxes of an image that is used at one time of an convolutional layer. So if you have a 3x3 filt...
H: What Introductory Statistics book would you recommend? Is there a particularly good book or good publisher for teaching Statistics from beginner level for someone interested in studying Data Science? AI: I would recommend Elements of Statistical Learning, by Trevor Hastie and Rob Tibshirani. That link gets the book...
H: train(): argument “x” is missing, with no default when i am trying the the following code I am getting an error: argument "x" is missing, with no default. > library(caret) Loading required package: ggplot2 Attaching package: ‘caret’ The following object is masked from ‘package:survival’: clus...
H: What to do if my target variable is column of lists? How I can transform my target variable(Y)? As it is list, I cann`t use it for fitting model, because I must use integers for fitting. AI: you can have multiple Y. Each item will be a binary variable which means that item exists or not.
H: How to aggregate data where instances occur over different time intervals I am working on a problem in which I have several instances that have predictors that have activity over various different time periods (i.e. <3 months to well over 20 months.) Originally I attempted to use knowledge I have about this problem...
H: Why fully calculate softmax? Why is the softmax activation function used in the output layer for CNNs? Why not just take the highest value of the units in the output layer? AI: If you are only interested in the most likely class, during inference you can skip the softmax. This is fairly common even, and the reason ...
H: What is the intuition behind Ridge Regression and Adapting Gradient Descent algorithms? So I was going through Adaptive Gradient Descent, and learning the intuition behind it: optimizing the learning algorithm, and getting the model to converge faster. The way AdaGrad does this, is by dividing the weight vector by ...
H: Experience replay in Reinforcement learning - Batch Size I am starting to understand Reinforcement Learning playing with the GYM Cart-pole environment. I would like to ask if the experience replay can slow down the training and if there is a maximum of the batch size? Maybe I misunderstood, and when the program sta...
H: What is the difference between fit() and fit_generator() in Keras? What is the difference between fit() and fit_generator() in Keras? When should I use fit() vs fit_generator()? AI: In keras, fit() is much similar to sklearn's fit method, where you pass array of features as x values and target as y values. You pass...
H: Why would you use word embeddings to find similar words? One of the applications of word embeddings (such as GloVe) is finding words of similar meaning. I just had a look at some embeddings produced by glove on large datasets and I found that the nearest neighbors of a given word are often fairly irrelevant. Eg. ‘d...
H: Inference of root mean square value in terms of house prediction The objective of the task is to predict the housing prices. A model is created based on California housing dataset to predict housing prices and is subjected to evaluation using the below code. from sklearn.metrics import mean_squared_error h...
H: How to extract particular key from the dict()? I have a dict() with 1000 keys. First 4 entries of dict are like. { 'aaa': [1,0,6,8,0,5,9,1,1,0], 'abc': [1,1,1,2,4,0,0,0,9,8], 'cfg': [0,0,0,4,3,1,0,0,0,1], 'cghjj': [7,8,9,2,3,0,0,0,0,0] } I want to create a dataset using each key one by one. I want...
H: How to transform dictionary data into a string vector? I have key,value data where each record is in a Python string. An example record looks like this: record = { 'first_name': 'john', 'last_name': 'doe', 'age': '50', } To encode this into a neural net, I would like to firs have this data as a string ...
H: How to show value of a classification model even though it doesn't get the desired performance? I developed a classification model for a telecom client. Where we classify between Dual-sim and non-Dual-Sim clients. After many iteration the best precision we can get is 60%. The contract says that the acceptance crite...
H: Titanic Kaggle Data: Why am I getting lower accuracy on Kaggle submissions than on held-out data? I am going through my first solo machine learning project and would like to gain some insight into what I am doing wrong/what is going on here as I am a bit stuck. I have been applying machine learning to the Titanic d...
H: Do Data Scientists prefer MACS? I see many Data Science (DS) tutorials done on MACS, and many DS blogs recommend MACS as the best developing platform, thus the quote "Data Science is statistics on a Mac" came more than once into my mind. I'm quite fascinated by MACS (be it iMAC or MacbookPro) but I never could get ...
H: Display images after augmentation in Keras How can I display all images after augmentation? How can I get the number of the trained data after augmentation? Thank you AI: Depending on the kind of data set you are using you can use .flow (if you have data as numpy arrays) or .flow_from_directory (if you have images ...
H: How to download a Jupyter Notebook from GitHub? This is a fairly basic question. I am working on a data science project inside of a Pandas tutorial. I can access my Jupyter notebooks through my Anaconda installation. The only problem is that the tutorial notebooks (exercise files) are on GitHub. My question: how do...
H: How to train convolutional neural networks on unbalanced datasets of images? How can I train convolutional neural networks on unbalanced datasets of images? My dataset has around 400 classes and the classes have different number of images.. AI: By oversampling. When training a CNN, you generally use a mini-batch gr...
H: What are the benefits and tradeoffs of a 1D conv vs a multi-input seq2seq LSTM model? I have 6 sequences, s1,..,s6. Using all sequences I want to predict a binary vector q = [0,0,0,1,1,1,0,0,0,1,1,1,...], which is a mask of the activity of the 6 sequences. I have looked at seq2seq lstm models, but am struggling wit...
H: Are there enough databases for all learning tasks? this might be a silly question but I guess the answer comes with experience in this field. I'm just wondering if today, with the internet overflowing with data and specifically with images (maybe not tagged), are there a lot of examples for learning tasks (specific...
H: How to Normalize a feature I have a feature that income of individual. It ranges from 10k to 116 Million. I have about 300k+ records. Clearly, I cannot use this feature as is as it will distort the model output and there are outliers.. I was thinking of normalizing all values from 0 to 1. And also eleminating outli...
H: time serie with only two values Could any one help me know about different approaches, methods or algorithms to build a model to forcast a time serie which has only two values ( 0, 1 ) but they last over time each time . basically I've some on/off data, it tell me if there is an object in a place and how much time...
H: What machine learning algorithms to use for unsupervised POS tagging? I am interested in an unsupervised approach to training a POS-tagger. Labeling is very difficult and I would like to test a tagger for my specific domain (chats) where users typically write in lower cases etc. If it matters, the data is mostly in...
H: It is helpful to normalize target variables for a regression neural network? It is customary to normalize feature variables and this normally does increase the performance of a neural network in particular a CNN. I was wondering if normalizing the target could also help increase performance? I did not notice an inc...
H: How to get windspeed when temperature is maximum for each city? Here is the sample dataset, I have Weather_Data, I want to calculate "What is the windspeed when temperature is maximum for each city" I have tried following code: df = pd.read_csv('weather_by_cities.csv') g = df.groupby('city') g.max() But Instead ...
H: Machine Learning for user modelling I have a dataset where each row is a interaction of a user with a content. I have user's features to represent the user (each user is uniquely represented through user.id): user.id, user.nationality, user.company, user.role and content's feature: content.id, content.type, conten...
H: Handling actions with delayed effect (Reinforcement learning) I am working on a problem where the action that I learn (using DQN) can be executed 'now' but it's effect on the environment is delayed by 'T' units of time. The environment however is active in that time and there are other conditions based on which rew...
H: Policy Gradients vs Value function, when implemented via DQN After studying Q-learning, Sarsa & DQN I've now discovered a term "Policy Gradients". It's a bit unclear to me how it differs to the above approaches. Here is my understanding, please correct it: From the moment I first encountered DQN, I always imagined...
H: Representing cyclical features as sin/cos components I'm working on a prediction project where we have a lot cyclical features such as hour of the day, weekday, month, day of year, etc etc. After some searching I decided to follow the advice here. Now I have the sin and cos component for every cyclical feature as a...
H: How to standarize feature vector with data in different scales? Let's suppose I have a dataset with numerical attributes of different types. Let's suppose I want to employ a Neural Network for supervised classification with that dataset. For that, I need to extract feature vectors from that data. Those feature vec...
H: Gini Index in Regression Decision Tree I want to implement my own version of the CART Decision Tree from scrach (to learn how it works) but I have some trouble with the Gini Index, used to express the purity of a dataset. More precisely, I don't understand how Gini Index is supposed to work in the case of a regress...
H: Why should re-sampling change the value of model's coefficients? I have the code below in python to create LinearRegression model. When I train the model with re-sampled data, I get different values for its coefficients. I can't understand why that happens. Can you help me in this please? [Update] I assume that r...
H: In CNN (Convolutional Neural Network), does the combination of previous layer's filters make next layer's filters? I know that the first layer uses a low-level filter to see the edge information. As the layer gets deeper, it will represent high-level (abstract) information. Is it because the combinations of filters...
H: Influence of a data point on the regression result? Let's say I perform multiple regression where y = income, x1 = educaiton, x2 = sex, and x3 = religion from 2003 to 2018, where the data is measured daily. Is there any way to quantify an impact of a single day data (e.x. 2005-07-01) on the regression result? AI: I...
H: Some confusions on Model selection using cross-validation approach https://stats.stackexchange.com/questions/11602/training-with-the-full-dataset-after-cross-validation explains the procedure and the importance of doing cross-validation to assess the performance of the method/ classifier. I have few concerns which ...
H: How would you deal with inf. or NA for rate or ratio as a feature variable I'm trying to create a feature for a churn model (binary classifier). The feature is mean of sales growth rates for several months. But if I just take the mean of sales for several months, I often get NAN or inf. since sales are often zeros...
H: I got 100% accuracy on my test set,is there something wrong? I got 100% accuracy on my test set when trained using decision tree algorithm.but only got 85% accuracy on random forest Is there something wrong with my model or is decision tree best suited for the dataset provided. Code: from sklearn.model_selection im...
H: Computational aspects are typically ignored by statisticians In the introductory chapter of "Process Mining: Data Science in Action" (2016 - Van der Aalst, pag 11) the author says that : Although data science can be seen as a continuation of statistics, the majority of statisticians did not contribute much to re...
H: How to select features for Text classification problem I am working on a problem where we need to classify user query into multiple classes. Problem: Suppose we are running a website for selling products. The website has a form where the user can write any complaint or issue. In order to resolve users issue, we th...
H: Labeling hubs in a network Let's say we did some analysis on a network dataset. We have an adjacency matrix which we can use to construct a graph and we can find the nodes with the highest degree's. How would I go about giving a location of these nodes. Would it be okay to refer to the entries of the adjacency matr...
H: Uninitialized Value Error in Tensorflow I am trying to build Encoder-Decoder which consists of down and upsampling Convolutional network with a reference to following article and its explanation: This is what I wrote down, but it keep returning uninitialized value error import tensorflow as tf import num...
H: Why is it bad to use the same test dataset over and over again? I am following this Google's series: Machine Learning Crash Course. On the chapter about generalisation, they make the following statement: Good performance on the test set is a useful indicator of good performance on the new data in general, assuming ...
H: How to deal with unbalanced class in biological datasets? When dealing with unbalanced class, which is better, oversampling/undersampling of the classes or randomly selecting equal number of positive samples and negative samples from the training dataset and combining as training samples, transforming the imbala...
H: How to handle NaNs for ratio feature for binary classifier? I'm creating a churn model and would like to create a ratio (# customers / total transaction) for each merchant. About 70% of the data are NaNs (zero/zero). I was wondering what I should impute for the 70% of the NaNs. I have other features and I don't li...
H: Convert nominal to numeric variables? I am trying to develeop an algorithm with sklearn and Tensorflow to predict which car can be offer to each customer. To do that I have a database with the answers of one survey to 1000 customers. An example of questions/[Answers] are: Color/[Green,Red,Blue] NumberOfPax/[2,4,5,...
H: Why does prediction by a consensus of classifier work better than prediction by a single classifiers? I have seen that consensus of classifiers (taking say 5 separate classifiers) and obtaining the final labeling of the unknown sample based on the voting method (whichever class gets the predicted the most is the cl...
H: What is the meaning of the term "pipeline" within data science? People often refer to pipelines when talking about models, data and even layers in a neural network. What can be meant by a pipeline? AI: A pipeline is almost like an algorithm, but at a higher level, in that it lists the steps of a process. People use...
H: Confusion about neural network architecture for the actor critic reinforcement learning algorithm I am trying to understand the implementation of the actor critic reinforcement learning algorithm. According to this, there should be just one neural network with two heads for the action probabilities and the state va...
H: Algorithm for backpropagation through time I am reading through this article trying to understand the bptt algorithm, in the context of an RNN. However there is one part I don’t understand: layer_1_delta = (future_layer_1_delta.dot(synapse_h.T) + layer_2_delta.dot(synapse_1.T)) + sigmoid_output_to_de...
H: How are data in tensorflow.examples.tutorials.mnist formatted? I am analyzing a sample code that implements a Restricted Boltzmann Machine (RBM) using Tensorflow. The input data seems to be the good old MNIST, except that apparently, it is now available in Tensorflow itself. So, instead of running this sample code ...
H: R error condition has length > 1 Hi i am getting this error: Error in if (x < min) { : missing value where TRUE/FALSE needed In addition: Warning message: In if (x < min) { : the condition has length > 1 and only the first element will be used I have seen this error in others post but his solutions don't ...
H: R - Order each matrix inside a list of matrices I have a list where each element is a matrix, and I want to order each matrix individually Order a matrix is as easy as this: data <- data[order(data$value),] But I am struggling to order a list of matrix individually I have tried this with some variations: for(i i...
H: How to choose the random seed? I understand this question can be strange, but how do I pick the final random_seed for my classifier? Below is an example code. It uses the SGDClassifier from SKlearn on the iris dataset, and GridSearchCV to find the best random_state: from sklearn.linear_model import SGDClassifier fr...
H: Database on time to churn in telecomunication I would like to research about time to churn1 in the telecommunication market. Does anyone have a link to such a database? The only ones I found did not include the time of churn, but only if a customer is labeled as churn or non-churn, what I would need is time to even...
H: Why is this TensorFlow CNN not generalising? So I wrote a TensorFlow CNN by creating manual layers. It is not state of art, but a simple experimental setup. The problem is it is not generalising well, it is hardly generalising. This should not be the case, it should at-least generalise somewhat. As you will see be...
H: CNN only performs well when split into 2 models I have 2 groups of data of equal shape (the main difference between the 2 are that one has half as many features - and consequently different labels of course)that perform better when they are trained independently (both using the same code). Is there any canonical ap...
H: Dealing with a dataset having target values on different scales? I am currently working on a dataset having 10 features and one continuous target variable. One of the features is 'Country' , in which there are seven unique values [Argentina ,Denmark , France...etc]. Now , the continuous target variable is sales of...
H: Calculate Q parameter for Deep Q-Learning applied to videogames I am working on Deep Q-learning applied to Snake, and I am confused on the methodology. Based on the DeepMind paper on the topic and other sources, the Q-value with the Bellman equation needs to be calculated as follows: Q(s,a) = r + γ(max(Q(s',a')) W...
H: laptops which are suitable for heavy Image and video processing I am a graduate student and My thesis is based on deep learning, vision, video and Image processing. I am going to do heavy computing and processing. I am looking for a compatible laptop which has a fast GPU-enabled laptop. CUDA enabled on an NVIDIA GP...
H: Keras- LSTM answers different size Imagine situation, input is some text file and information are spread according to rows. I want to use rows as input of model. Model is planned as LSTM with softmax as output layer. My problem is the output; I want to classify text file to some categories. So I imagine this like, ...
H: How to calculate precision and recall in an unsupervised ranking method in order to be compared with a supervised one? I am working on an ML supervised learning project for Key-phrase extraction. The evaluation dataset (different from training-validation datasets) contains around 200 phrases labeled as key or not k...
H: 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: [{'word': 'are', 'lemma': 'be', 'NE': '', 'POS_fine': 'VBP', 'POS_coarse': 'VERB', 'arc': 'ROOT', 'modifiers': ...
H: Is it possible to make tensorflow print out everything it see in a given image and not just the top five results? I'm working through the python API tutorials for Tensorflow and I'm seeing the results that are normally displayed, but it's always giving me the top five results. I'm trying to discern all possibilitie...
H: Retraining a machine learning model Created a Machine Learning model on some data. Used this model for predicting test data. Model has learnt only from training data. How this model can be retrained as new data come in for prediction. I don't know whether it is true that retraining a model is necessary so that it c...
H: Aggregating standard deviations Imagine I have a collection of data, let's say the travel time for a road segment. On this collection I want to calculate the mean and the standard deviation. Nothing hard so far. Now imagine that instead of having my collection of values for one road segment, I have multiple collect...
H: How to populate pandas series w/ values from another df? I need help figuring out how to populate a series of one dataframe w/ specific values from another dataframe. Here's a sample of what I'm working with: df1 = pd.DataFrame({'Year':[1910, 1911, 1912], 'CA':[2.406, 2.534, 2.668], ...
H: Setting up network communication between R and Python I want to share data between R and python via network sockets (I expect the solution to also work for R-R and python-python). I am interested in server being both R and Python side. For now I am interested in a simpler case of synchronous connections. What are t...
H: Data scaling before or after PCA I have seen senior data scientists doing data scaling either before or after applying PCA. What is more right to do and why? AI: I once heard a data scinetist state at a conference talk: "Basically, you can do what you want, as long as you know what you are doing." This also applie...
H: Categorical data for sklearns Isolation Forrest I'm trying to do anomaly detection with Isolation Forests (IF) in sklearn. Except for the fact that it is a great method of anomaly detection, I also want to use it because about half of my features are categorical (font names, etc.) I've got a bit too much to use one...
H: Confusion regarding epoch and accuracy I have been learning keras and TensorFlow for some weeks now, and get confused with epoch. I trained my network for 50 epochs, the test data and training data are randomly split (80% train, 20% test). The training data's accuracy grows nicely, but the test data's accuracy goes...
H: Should we keep all channels when doing image classification? I am discovering the world of image recognition and now trying to build an image classifier. The set of images I have have the shape (101,101,3) which means that it has 3 channels. If I'm not mistaken the channels corresponds to the Red, Green and Blue ch...
H: Is there a general guideline for experience replay size, and how to store? I am trying to use deep Q-learning on color images of size (224 x 224 x 3). I have read that implementations of DQN use experience replay sizes around 50,000. If my calculation is correct, this is over 56 Gigabytes for my data (two images pe...
H: What is coadaptation of neurons in neural networks? Looking for a bare minimum example (3 hidden units only maybe?) for what weights of a neural network with heavily coadapted weights would look like and showcase why they are bad. Also, how is coadaptation a sign of overfitting? AI: Co-adaptions in simple English t...
H: How to apply StandardScaler and OneHotEncoder simultaneously in Spark Machine learning? I try to create a machine learning model, linear regression, to predict a price of a diamonds. All examples that I found online do not have a step with scaling of data, using MinMaxScaler or StandardScaler. But I personally thi...
H: How to adjust the hyperparameters of MLP classifier to get more perfect performance I am just getting touch with Multi-layer Perceptron. And, I got this accuracy when classifying the DEAP data with MLP. However, I have no idea how to adjust the hyperparameters for improving the result. Here is the detail of my cod...
H: Improve results of a clustering I'm a beginner and I'm trying to do a clustering of a multi-sentence text, but my results are horrible. Any tips for me to improve my result? import pandas import pprint import numpy as np import pandas as pd from sklearn.cluster import KMeans from sklearn.metrics import adjusted_ran...
H: Do we need the testing data to evaluate the Model Performance - Regression I have been working with Classification Modelling in R and Python for the last 6 months now. With the Classification, the evaluation of the Model was based on Precision, Recall, Hamming Loss, accuracy etc., These classification models neede...
H: Is K-NN applicable for binary variables? I need help because I'm just new to machine learning and I do not know if k-nearest neighbors algorithm can be used to identify the appropriate program(s) for Student 11 in the table below. The school subjects (Math, English, etc.) are the features, while the 'Program' colu...
H: Active Mask - image segmentation I'm trying to implement an active mask code derived from Active mask segmentation for the cell-volume computation and golgi-body segmentation of hela cell images, Srinivasa et al 2008. I have found a code that will allow me to do this, however, there is one section of the code that ...
H: Image classification with different number of training image for each class I'm trying to train neural network for image classification with 4 different classes: Cars (22k training examples) Building (8k training examples) Pedestrian (5k training examples) Trees (1k training examples) The problem is that the numb...
H: Cosine similarity between two folders (1 and 2) with documents, and find the most relevant set of documents (in folder 2) for each doc (in folder 2) I have one folder named iir, it has 500 txt files. I have another json file named video (with dictionary structure). I wish to compute: for each of the 500 txt files, ...
H: what does this doc2vec based ML predict? I'm trying to understand what does this ML program - which based on doc2vec - predict: import logging, gensim from gensim.models.doc2vec import TaggedDocument from gensim.models import Doc2Vec import re import os import random from sklearn.metrics.pairwise import cosine_...
H: Sparse Data Interpolation I have a price data set where on some days there are up to five data points and some days none at all. For example: 2.110 2017-04-19 1.910 2017-04-23 1.980 2017-04-24 1.980 2017-04-24 1.980 2017-04-24 1.230 2017-04-24 2.100 2017-05-04 1.920 2017-05-08 The t...
H: How the term "R-squared" in VIF(variance inflation factor) is different from normal R-squared calculation? In normal calculation of R2 , more the value of R2 , it indicates variable represents more variance across the dataset. But in the calculation of VIF (variance inflation factor), higher the value of R2 , more ...
H: Maths question on mean squared error being dervied to bias and variance I am reading a book and have difficulty in understanding the math on bias- variance tradeoff. Below is the section that I am having trouble with: Given a set of training samples $x_1, x_2, ..., x_n$ and their targets $y_1, y_2, ..., y_n$, we w...
H: storing a huge dataset in h5py file format I work on preparing the luna16 dataset for feeding into the CNN model, after reading all '.mhd' files and the labels(0, 1) in the annotated CSV file, I get a memory error, I know the problem is because of the data size is need a lot of RAM that I do not have on my computer...
H: How do I remove outliers from my data? Should I use RobustScaler? I am aware I can use DecisionTree but I want to use XGBoost How do I remove outliers from my data? Should I use RobustScaler? I am aware I can use DecisionTree but I want to use XGBoost... Please can you help me, This is a bit urgent, I am not sure h...
H: Are dimensionality reduction techniques useful in deep learning I have been working on machine learning and noticed that most of the time, dimensionality reduction techniques like PCA and t-SNE are used in machine learning, but I rarely noticed anyone doing it for deep learning projects. Is there a specific reason ...
H: how to represent location-code as a feature in machine learning model? I am trying to predict the damage to a buildings after earthquake on a dataset which contains "district number" as feature. I think the feature will have a significant importance in predicting the label but I am not sure how to best represent it...
H: Error not decreasing in a 3 layer deep CNN using TensorFlow I'm trying to train a CNN to play an online game by feeding images of the game along with the keyboard input. By playing the game for some time and collecting the data, I gathered 342 images with size 110x42. I'm feeding these images in the network like so...
H: classification performance metric for high risk medical decisions What is the best classification performance metric for risky medical treatments like surgery? for example a patient should NOT suggest a surgery (negative) if he/she can be treated by medicine (positive). Does Negative predictive value (TN/TN+FN) wor...