CHIRAG's_DataCafe

What is a Support Vector Machine?  1.)  It is a supervised machine learning problem where we try to find a hyperplane that best separates the two classes.   2.) Support Vector Machines   (SVMs in short) are machine learning algorithms that are used for classification and regression purposes. SVMs are one of the powerful machine learning algorithms for classification, regression and outlier detection purposes.  3.)  An SVM classifier builds a model that assigns new data points to one of the given categories.   4.)Thus, it can be viewed as a non-probabilistic binary linear classifier.   Don’t get confused between SVM and logistic regression. Both the algorithms try to find the best hyperplane, but the main difference is logistic regression is a probabilistic approach whereas support vector machine is based on statistical approaches. Support Vector Machines intuition   Now, we should be familiar with some SVM terminology. Hyperplane A hyperplane...

  What is Overfitting? Overfitting means model has High accuracy score on training data but low accuracy score on test data. (That means our model best fit line satisfied all the training data points . ie. Low Training Error & High Testing Error & High Training Accuracy & Low Test Accuracy ) Reasons for Overfitting:   High variance(High Test Error) .  Low Bias(Low Training Error). The model is too complex. The size of the training data. What is Bias? Bias is the difference between the average prediction of our model and the correct value which we are trying to predict. A model with high bias pays very little attention to the training data and oversimplifies the model. Let’s assume we have trained the model and are trying to predict values with input ‘x_train’. The predicted values are y_predicted.  Bias is the error rate of y_predicted and y_train. In simple terms.   think of bias as the error rate of the training data. When the error rate is high,...

DEFINITION A VIEW in SQL Server is like a virtual table that contains data from one or multiple tables. It does not hold any data and does not exist physically in the database. Similar to a SQL table, the view name should be unique in a database.  It contains a set of predefined SQL queries to fetch data from the database. It can contain database tables from single or multiple databases as well. A VIEW does not require any storage in a database because it does not exist physically How Does an SQL View Work? A table (concrete table) stores its data in columns and rows in the database. A view (virtual table) is built on top of the concrete table(s) it fetches data from and does not store any data of its own in the database. A view only contains the SQL query that is used to fetch the data. To summarize, the result set of a view is not materialized on the disk, and the query stored by the view is run every time we call the view. Let’s look at the diagram below to understand the differ...