In today’s world, it is driven by technology. Technology is advancing day by day. Coding plays an important role in these changes. Coding plays a key role in the day to day life. The device we use in daily life from smartphones to automated cars all are running with the help of coding and technology. Technology is something that drives us towards a fast and efficient world. The introduction of Artificial Intelligence gave a great boost to technology.
Machine Learning is a branch of Artificial Intelligence. It focuses on data and algorithms. It uses data and algorithms to learn the way how humans learn. Machine Learning and Artificial Intelligence learn things themselves using data and algorithms. They improve accuracy by constant learning. That is why their application is everywhere. Almost all industries run with the help of machine learning and artificial intelligence.
In the field of data science, machine learning has a long impact and it has more importance. Machine learning uses statistical methods and algorithms for making predictions or exposing key insights of data mining projects. These insights are used to make decisions in businesses. In earlier days this data mining or data analysis was done manually and it was time-consuming. But time has gone and now the data size is unimaginable. Huge data cannot be handled manually within time. For making this heavy process fast and reliable machine learning will help. Machine learning will analyze data with algorithms and statistical tools and helps the business to make decisions on time.
Let us look at how Machine learning works. The learning system of machine learning is divided into three. They are:
- Decision Process
In general terms, we can conclude that machine learning helps in making predictions and classifications. With the data which has to be analyzed, machine learning will make conclusions and it will be communicated to the business. These conclusions help the business to make decisions.
- Error Function
We know machine learning deals with predictions or classifications. This error function helps in evaluating the predictions. By doing this the accuracy of the predictions can be assessed.
- Model Optimization Process
The optimization process as the name suggests is the optimization of the known example and the model estimate. By optimizing, any discrepancies can be found. The optimization process is repeated by the algorithm to make sure the accuracy of the model has been met.
These are the three working processes or stages of Machine learning. This is how it makes accurate predictions and classifications.
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KNN Algorithm in Machine Learning
KNN Algorithm simply means k-nearest neighbors algorithm. It is one of the easy Machine learning algorithms. It assumes the similarity between the new cases and available cases. It put the new case to the available case that is similar to the available case. It stores all available data. It stores the new data based on similarity. KNN algorithm can be said as non-parametric. That is, it does not make any presumptions about the fundamental data. This algorithm is mostly used for category problems. It is also used for the regression process.
KNN Algorithm is called a lazy learner algorithm. It doesn’t learn things immediately from the training set. Instead, it stores datasets and learns from them. In the training phase, the KNN algorithm just saves the data set, and when it gets new data it adds the data to the data set which is similar to the data set. That is why it is called a lazy learner algorithm. There are some steps to knowing how KNN Algorithm works. They are:
- Select the number K from the neighbors
- Calculate the Euclidean Distance
- Take the K nearest neighbors
- Gauge the numeral of data points in each category
- Assign new data points
- Model is ready
In the KNN algorithm, the Euclidean distance is calculated using the KNN algorithm formula.
Machine learning is updating day by day and it is now a key part of the classification, prediction, and decision making. The KNN algorithm is the simplest in machine learning. It is also learning but not in the training phase. But it classifies new data sets as similar data sets already have. So KNN algorithm is a key part of machine learning in terms of decision making.
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