Explore Courses
Liverpool Business SchoolLiverpool Business SchoolMBA by Liverpool Business School
  • 18 Months
Bestseller
Golden Gate UniversityGolden Gate UniversityMBA (Master of Business Administration)
  • 15 Months
Popular
O.P.Jindal Global UniversityO.P.Jindal Global UniversityMaster of Business Administration (MBA)
  • 12 Months
New
Birla Institute of Management Technology Birla Institute of Management Technology Post Graduate Diploma in Management (BIMTECH)
  • 24 Months
Liverpool John Moores UniversityLiverpool John Moores UniversityMS in Data Science
  • 18 Months
Popular
IIIT BangaloreIIIT BangalorePost Graduate Programme in Data Science & AI (Executive)
  • 12 Months
Bestseller
Golden Gate UniversityGolden Gate UniversityDBA in Emerging Technologies with concentration in Generative AI
  • 3 Years
upGradupGradData Science Bootcamp with AI
  • 6 Months
New
University of MarylandIIIT BangalorePost Graduate Certificate in Data Science & AI (Executive)
  • 8-8.5 Months
upGradupGradData Science Bootcamp with AI
  • 6 months
Popular
upGrad KnowledgeHutupGrad KnowledgeHutData Engineer Bootcamp
  • Self-Paced
upGradupGradCertificate Course in Business Analytics & Consulting in association with PwC India
  • 06 Months
OP Jindal Global UniversityOP Jindal Global UniversityMaster of Design in User Experience Design
  • 12 Months
Popular
WoolfWoolfMaster of Science in Computer Science
  • 18 Months
New
Jindal Global UniversityJindal Global UniversityMaster of Design in User Experience
  • 12 Months
New
Rushford, GenevaRushford Business SchoolDBA Doctorate in Technology (Computer Science)
  • 36 Months
IIIT BangaloreIIIT BangaloreCloud Computing and DevOps Program (Executive)
  • 8 Months
New
upGrad KnowledgeHutupGrad KnowledgeHutAWS Solutions Architect Certification
  • 32 Hours
upGradupGradFull Stack Software Development Bootcamp
  • 6 Months
Popular
upGradupGradUI/UX Bootcamp
  • 3 Months
upGradupGradCloud Computing Bootcamp
  • 7.5 Months
Golden Gate University Golden Gate University Doctor of Business Administration in Digital Leadership
  • 36 Months
New
Jindal Global UniversityJindal Global UniversityMaster of Design in User Experience
  • 12 Months
New
Golden Gate University Golden Gate University Doctor of Business Administration (DBA)
  • 36 Months
Bestseller
Ecole Supérieure de Gestion et Commerce International ParisEcole Supérieure de Gestion et Commerce International ParisDoctorate of Business Administration (DBA)
  • 36 Months
Rushford, GenevaRushford Business SchoolDoctorate of Business Administration (DBA)
  • 36 Months
KnowledgeHut upGradKnowledgeHut upGradSAFe® 6.0 Certified ScrumMaster (SSM) Training
  • Self-Paced
KnowledgeHut upGradKnowledgeHut upGradPMP® certification
  • Self-Paced
IIM KozhikodeIIM KozhikodeProfessional Certification in HR Management and Analytics
  • 6 Months
Bestseller
Duke CEDuke CEPost Graduate Certificate in Product Management
  • 4-8 Months
Bestseller
upGrad KnowledgeHutupGrad KnowledgeHutLeading SAFe® 6.0 Certification
  • 16 Hours
Popular
upGrad KnowledgeHutupGrad KnowledgeHutCertified ScrumMaster®(CSM) Training
  • 16 Hours
Bestseller
PwCupGrad CampusCertification Program in Financial Modelling & Analysis in association with PwC India
  • 4 Months
upGrad KnowledgeHutupGrad KnowledgeHutSAFe® 6.0 POPM Certification
  • 16 Hours
O.P.Jindal Global UniversityO.P.Jindal Global UniversityMaster of Science in Artificial Intelligence and Data Science
  • 12 Months
Bestseller
Liverpool John Moores University Liverpool John Moores University MS in Machine Learning & AI
  • 18 Months
Popular
Golden Gate UniversityGolden Gate UniversityDBA in Emerging Technologies with concentration in Generative AI
  • 3 Years
IIIT BangaloreIIIT BangaloreExecutive Post Graduate Programme in Machine Learning & AI
  • 13 Months
Bestseller
IIITBIIITBExecutive Program in Generative AI for Leaders
  • 4 Months
upGradupGradAdvanced Certificate Program in GenerativeAI
  • 4 Months
New
IIIT BangaloreIIIT BangalorePost Graduate Certificate in Machine Learning & Deep Learning (Executive)
  • 8 Months
Bestseller
Jindal Global UniversityJindal Global UniversityMaster of Design in User Experience
  • 12 Months
New
Liverpool Business SchoolLiverpool Business SchoolMBA with Marketing Concentration
  • 18 Months
Bestseller
Golden Gate UniversityGolden Gate UniversityMBA with Marketing Concentration
  • 15 Months
Popular
MICAMICAAdvanced Certificate in Digital Marketing and Communication
  • 6 Months
Bestseller
MICAMICAAdvanced Certificate in Brand Communication Management
  • 5 Months
Popular
upGradupGradDigital Marketing Accelerator Program
  • 05 Months
Jindal Global Law SchoolJindal Global Law SchoolLL.M. in Corporate & Financial Law
  • 12 Months
Bestseller
Jindal Global Law SchoolJindal Global Law SchoolLL.M. in AI and Emerging Technologies (Blended Learning Program)
  • 12 Months
Jindal Global Law SchoolJindal Global Law SchoolLL.M. in Intellectual Property & Technology Law
  • 12 Months
Jindal Global Law SchoolJindal Global Law SchoolLL.M. in Dispute Resolution
  • 12 Months
upGradupGradContract Law Certificate Program
  • Self paced
New
ESGCI, ParisESGCI, ParisDoctorate of Business Administration (DBA) from ESGCI, Paris
  • 36 Months
Golden Gate University Golden Gate University Doctor of Business Administration From Golden Gate University, San Francisco
  • 36 Months
Rushford Business SchoolRushford Business SchoolDoctor of Business Administration from Rushford Business School, Switzerland)
  • 36 Months
Edgewood CollegeEdgewood CollegeDoctorate of Business Administration from Edgewood College
  • 24 Months
Golden Gate UniversityGolden Gate UniversityDBA in Emerging Technologies with Concentration in Generative AI
  • 36 Months
Golden Gate University Golden Gate University DBA in Digital Leadership from Golden Gate University, San Francisco
  • 36 Months
Liverpool Business SchoolLiverpool Business SchoolMBA by Liverpool Business School
  • 18 Months
Bestseller
Golden Gate UniversityGolden Gate UniversityMBA (Master of Business Administration)
  • 15 Months
Popular
O.P.Jindal Global UniversityO.P.Jindal Global UniversityMaster of Business Administration (MBA)
  • 12 Months
New
Deakin Business School and Institute of Management Technology, GhaziabadDeakin Business School and IMT, GhaziabadMBA (Master of Business Administration)
  • 12 Months
Liverpool John Moores UniversityLiverpool John Moores UniversityMS in Data Science
  • 18 Months
Bestseller
O.P.Jindal Global UniversityO.P.Jindal Global UniversityMaster of Science in Artificial Intelligence and Data Science
  • 12 Months
Bestseller
IIIT BangaloreIIIT BangalorePost Graduate Programme in Data Science (Executive)
  • 12 Months
Bestseller
O.P.Jindal Global UniversityO.P.Jindal Global UniversityO.P.Jindal Global University
  • 12 Months
WoolfWoolfMaster of Science in Computer Science
  • 18 Months
New
Liverpool John Moores University Liverpool John Moores University MS in Machine Learning & AI
  • 18 Months
Popular
Golden Gate UniversityGolden Gate UniversityDBA in Emerging Technologies with concentration in Generative AI
  • 3 Years
Rushford, GenevaRushford Business SchoolDoctorate of Business Administration (AI/ML)
  • 36 Months
Ecole Supérieure de Gestion et Commerce International ParisEcole Supérieure de Gestion et Commerce International ParisDBA Specialisation in AI & ML
  • 36 Months
Golden Gate University Golden Gate University Doctor of Business Administration (DBA)
  • 36 Months
Bestseller
Ecole Supérieure de Gestion et Commerce International ParisEcole Supérieure de Gestion et Commerce International ParisDoctorate of Business Administration (DBA)
  • 36 Months
Rushford, GenevaRushford Business SchoolDoctorate of Business Administration (DBA)
  • 36 Months
Liverpool Business SchoolLiverpool Business SchoolMBA with Marketing Concentration
  • 18 Months
Bestseller
Golden Gate UniversityGolden Gate UniversityMBA with Marketing Concentration
  • 15 Months
Popular
Jindal Global Law SchoolJindal Global Law SchoolLL.M. in Corporate & Financial Law
  • 12 Months
Bestseller
Jindal Global Law SchoolJindal Global Law SchoolLL.M. in Intellectual Property & Technology Law
  • 12 Months
Jindal Global Law SchoolJindal Global Law SchoolLL.M. in Dispute Resolution
  • 12 Months
IIITBIIITBExecutive Program in Generative AI for Leaders
  • 4 Months
New
IIIT BangaloreIIIT BangaloreExecutive Post Graduate Programme in Machine Learning & AI
  • 13 Months
Bestseller
upGradupGradData Science Bootcamp with AI
  • 6 Months
New
upGradupGradAdvanced Certificate Program in GenerativeAI
  • 4 Months
New
KnowledgeHut upGradKnowledgeHut upGradSAFe® 6.0 Certified ScrumMaster (SSM) Training
  • Self-Paced
upGrad KnowledgeHutupGrad KnowledgeHutCertified ScrumMaster®(CSM) Training
  • 16 Hours
upGrad KnowledgeHutupGrad KnowledgeHutLeading SAFe® 6.0 Certification
  • 16 Hours
KnowledgeHut upGradKnowledgeHut upGradPMP® certification
  • Self-Paced
upGrad KnowledgeHutupGrad KnowledgeHutAWS Solutions Architect Certification
  • 32 Hours
upGrad KnowledgeHutupGrad KnowledgeHutAzure Administrator Certification (AZ-104)
  • 24 Hours
KnowledgeHut upGradKnowledgeHut upGradAWS Cloud Practioner Essentials Certification
  • 1 Week
KnowledgeHut upGradKnowledgeHut upGradAzure Data Engineering Training (DP-203)
  • 1 Week
MICAMICAAdvanced Certificate in Digital Marketing and Communication
  • 6 Months
Bestseller
MICAMICAAdvanced Certificate in Brand Communication Management
  • 5 Months
Popular
IIM KozhikodeIIM KozhikodeProfessional Certification in HR Management and Analytics
  • 6 Months
Bestseller
Duke CEDuke CEPost Graduate Certificate in Product Management
  • 4-8 Months
Bestseller
Loyola Institute of Business Administration (LIBA)Loyola Institute of Business Administration (LIBA)Executive PG Programme in Human Resource Management
  • 11 Months
Popular
Goa Institute of ManagementGoa Institute of ManagementExecutive PG Program in Healthcare Management
  • 11 Months
IMT GhaziabadIMT GhaziabadAdvanced General Management Program
  • 11 Months
Golden Gate UniversityGolden Gate UniversityProfessional Certificate in Global Business Management
  • 6-8 Months
upGradupGradContract Law Certificate Program
  • Self paced
New
IU, GermanyIU, GermanyMaster of Business Administration (90 ECTS)
  • 18 Months
Bestseller
IU, GermanyIU, GermanyMaster in International Management (120 ECTS)
  • 24 Months
Popular
IU, GermanyIU, GermanyB.Sc. Computer Science (180 ECTS)
  • 36 Months
Clark UniversityClark UniversityMaster of Business Administration
  • 23 Months
New
Golden Gate UniversityGolden Gate UniversityMaster of Business Administration
  • 20 Months
Clark University, USClark University, USMS in Project Management
  • 20 Months
New
Edgewood CollegeEdgewood CollegeMaster of Business Administration
  • 23 Months
The American Business SchoolThe American Business SchoolMBA with specialization
  • 23 Months
New
Aivancity ParisAivancity ParisMSc Artificial Intelligence Engineering
  • 24 Months
Aivancity ParisAivancity ParisMSc Data Engineering
  • 24 Months
The American Business SchoolThe American Business SchoolMBA with specialization
  • 23 Months
New
Aivancity ParisAivancity ParisMSc Artificial Intelligence Engineering
  • 24 Months
Aivancity ParisAivancity ParisMSc Data Engineering
  • 24 Months
upGradupGradData Science Bootcamp with AI
  • 6 Months
Popular
upGrad KnowledgeHutupGrad KnowledgeHutData Engineer Bootcamp
  • Self-Paced
upGradupGradFull Stack Software Development Bootcamp
  • 6 Months
Bestseller
KnowledgeHut upGradKnowledgeHut upGradBackend Development Bootcamp
  • Self-Paced
upGradupGradUI/UX Bootcamp
  • 3 Months
upGradupGradCloud Computing Bootcamp
  • 7.5 Months
PwCupGrad CampusCertification Program in Financial Modelling & Analysis in association with PwC India
  • 5 Months
upGrad KnowledgeHutupGrad KnowledgeHutSAFe® 6.0 POPM Certification
  • 16 Hours
upGradupGradDigital Marketing Accelerator Program
  • 05 Months
upGradupGradAdvanced Certificate Program in GenerativeAI
  • 4 Months
New
upGradupGradData Science Bootcamp with AI
  • 6 Months
Popular
upGradupGradFull Stack Software Development Bootcamp
  • 6 Months
Bestseller
upGradupGradUI/UX Bootcamp
  • 3 Months
PwCupGrad CampusCertification Program in Financial Modelling & Analysis in association with PwC India
  • 4 Months
upGradupGradCertificate Course in Business Analytics & Consulting in association with PwC India
  • 06 Months
upGradupGradDigital Marketing Accelerator Program
  • 05 Months

Classification Model using Artificial Neural Networks (ANN)

Updated on 28 February, 2024

15.32K+ views
7 min read

In the machine learning terminology, classification model using artificial neural networks refers to a predictive modelling problem where the input data is classified as one of the predefined labelled classes.For example, predicting Yes or No, True or False falls in the category of Binary Classification as the number of outputs are limited to two labels.

Similarly, output having multiple classes like classifying different age groups are called multiclass classification problems. Classification problems are one of the most commonly used or defined types of ML problem that can be used in various use cases. There are various Machine Learning models that can be used for classification problems.

Ranging from Bagging to Boosting techniques although ML is more than capable of handling classification use cases, Neural Networks come into picture when we have a high amount of output classes and high amount of data to support the performance of the model. Going forward we’ll look at how we can implement a Classification Model using Neural Networks on Keras (Python). 

Learn Artificial Intelligence Course from the World’s top Universities. Earn Masters, Executive PGP, or Advanced Certificate Programs to fast-track your career.

Neural Networks

Neural networks are loosely representative of the human brain learning. An Artificial Neural Network consists of Neurons which in turn are responsible for creating layers. These Neurons are also known as tuned parameters.

The output from each layer is passed on to the next layer. There are different nonlinear activation functions to each layer, which helps in the learning process and the output of each layer. The output layer is also known as terminal neurons.

Source: Wikipedia

The weights associated with the neurons and which are responsible for the overall predictions are updated on each epoch. The learning rate is optimised using various optimisers. Each Neural Network is provided with a cost function which is minimised as the learning continues. The best weights are then used on which the cost function is giving the best results.

Read: TensorFlow Object Detection Tutorial For Beginners

Classification Problem

For this article, we will be using Keras to build the Neural Network. Keras can be directly imported in python using the following commands.

import tensorflow as tf

from tensorflow import keras

from keras.models import Sequential

from keras.layers import Dense

FYI: Free Deep Learning Course!

Dataset and Target variable

We will be using Diabetes dataset which will be having the following features:

Input Variables (X):

  • Pregnancies: Number of times pregnant
  • Glucose: Plasma glucose concentration a 2 hours in an oral glucose tolerance test
  • BloodPressure: Diastolic blood pressure (mm Hg)
  • SkinThickness: Triceps skin fold thickness (mm)
  • Insulin: 2-Hour serum insulin (mu U/ml)
  • BMI: Body mass index (weight in kg/(height in m)^2)
  • DiabetesPedigreeFunction: Diabetes pedigree function
  • Age: Age (years)

Output Variables (y):

Outcome: Class variable (0 or 1) [Patient is having Diabetes or not]

# load the dataset

df= loadtxt(‘pima-indians-diabetes.csv’, delimiter=’,’)

# Split data into X (input) and Y (output)

X = dataset[:,0:8]

y = dataset[:,8]

Define Keras Model

We can start building the classification model using artificial neural networks using sequential models. This top down approach helps build a Neural net architecture and play with the shape and layers. The first layer will have the number of features which can be fixed using input_dim. We will set it to 8 in this condition.

Creating Neural Networks is not a very easy process. There are many trials and errors that take place before a good model is built. We will build a Fully Connected network structure using the Dense class in keras. The Neuron counts as the first argument to be provided to the dense layer.

The activation function can be set using the activation argument. We will use the Rectified Linear Unit as the activation function in this case. There are other options like Sigmoid or TanH, but RELU is a very generalised and a better option.

# define the keras model

model = Sequential()

model.add(Dense(12, input_dim=8, activation=’relu’))

model.add(Dense(8, activation=’relu’))

model.add(Dense(1, activation=’sigmoid’))

Compile Keras Model

Compiling the model is the next step after model definition when creating a classification model using artificial neural networks. Tensorflow is utilized for model compilation, a crucial phase where parameters are defined for the model’s training and predictions. The process can leverage CPU/GPU or distributed memories in the background for efficient computation.

We have to specify a loss function which is used to evaluate weights for the different layers. The optimiser adjusts the learning rate and goes through various sets of weights. Binary Cross Entropy is chosen as the loss function due to its efficacy in classification models using artificial neural networks. For the optimizer, ADAM, known for its efficient stochastic gradient descent properties, is selected.

It is very popularly used for tuning. Finally, because it is a classification problem, we will collect and report the classification accuracy, defined via the metrics argument. We will use accuracy in this case.

# compile the keras model

model.compile(loss=’binary_crossentropy’, optimizer=’adam’, metrics=[‘accuracy’])

Model fit and Evaluation

Fitting the model is essentially known as model training. After Compiling the model, the model is ready to efficiently go over the data and train itself. The fit() function from Keras can be used for the process of model training. The two main parameters used before model training are:

  1. Epochs: One pass through the whole dataset.
  2. Batch Size: Weights are updated at each batch size. Epochs consist of equally distributed batches of data.

# fit the keras model on the dataset

model.fit(X, y, epochs=150, batch_size=10)

A GPU or a CPU is used in this process. The training can be a very long process depending on the epochs, batch size and most importantly the size of Data.

We can also evaluate the model on the training dataset using the evaluate() function. The data can be divided into training and testing sets and testing X and Y can be used for model evaluation. 

For each input and output pair, this will produce a forecast and gather scores, including the average loss and any measurements we have installed, such as precision. 

Also Read: Neural Network Model Introduction

A list of two values will be returned by the evaluate() function. The first will be the model loss on the dataset and the second will be the model’s accuracy on the dataset. We are only interested in the accuracy of the report, so we will disregard the importance of the loss.

# evaluate the keras model

_, accuracy = model.evaluate(Xtest, ytest)

print(‘Accuracy: %.2f’ % (accuracy*100))

Conclusion

The journey through creating a classification model using artificial neural networks (ANN) underscores the transformative power of this technology in tackling classification problems. ANN’s ability to learn from complex datasets and make accurate predictions has proven to be a game-changer in data science and machine learning. This exploration has highlighted not only the theoretical aspects but also the practical applications of neural networks in classifying data with precision and efficiency. As we’ve seen, the adaptability and scalability of ANN make it an indispensable tool for professionals looking to harness the potential of artificial intelligence in solving real-world problems. Whether you’re a novice stepping into the world of AI or a seasoned expert refining your skills, the journey of mastering Classification Models using Artificial Neural Networks promises a rewarding blend of challenges and breakthroughs, paving the way for future innovations in the domain. 

Checkout upGrad’s Advanced Certificate Programme in Machine Learning & NLP. This course has been crafted keeping in mind various kinds of students interested in Machine Learning, offering 1-1 mentorship and much more.

Frequently Asked Questions (FAQs)

1. How can neural networks be used for classification?

Classification is about categorizing objects into groups. A type of classification is where multiple classes are predicted. In neural networks, neural units are organized into layers. In the first layer, the input is processed and an output is produced. This output is then sent through the remaining layers to produce the final output. The same input is processed through the layer to produce different outputs. This can be represented with a multi-layer perceptron. The type of neural network used for classification depends on the data set, but neural networks have been used for classification problems.

2. Why are artificial neural networks good for classification?

In order to answer this question, we need to understand the basic principle of neural networks and the problem that neural networks are designed to solve. As the name suggests, neural networks are a biologically inspired model of the human brain. The basic idea is that we want to model a neuron as a mathematical function. Every neuron takes inputs from other neurons and computes an output. Then we connect these neurons in a way that mimics the neural network in the brain. The objective is to learn a network that can take in some data and produce an appropriate output.

3. When should we use Artificial Neural Networks?

Artificial Neural Networks are used in situations where you’re trying to duplicate the performance of living organisms or detect patterns in data. Medical diagnoses, recognizing speech, visualizing data, and predicting handwritten digits are all good use cases for an ANN. Artificial neural networks are used when there is a need to understand complex relationships between inputs and outputs. For example, there may be a lot of noise in the variables and it may be difficult to understand the relationships between these variables. Therefore, using Artificial Neural Networks is a common practice to retain the knowledge and data.