Fitting a Gradient Boosting Model - Learn how to fit a gradient boosting model and use your model to score new data In Part 6, Part 7, and Part 9 of this series, we fit a logistic regression, decision tree and random forest model to the Home Equity data we
Learn how to fit a random forest and use your model to score new data. In Part 6 and Part 7 of this series, we fit a logistic regression and decision tree to the Home Equity data we saved in Part 4. In this post we will fit a Random
Comparing Logistic Regression and Decision Tree - Which of our models is better at predicting our outcome? Learn how to compare models using misclassification, area under the curve (ROC) charts, and lift charts with validation data. In part 6 and part 7 of this series we fit a logistic regression
Learn how to fit a decision tree and use your decision tree model to score new data. In Part 6 of this series we took our Home Equity data saved in Part 4 and fit a logistic regression to it. In this post we will use the same data and
Learn how to fit a logistic regression and use your model to score new data. In part 4 of this series, we created and saved our modeling data set with all our updates from imputing missing values and assigning rows to training and validation data. Now we will use this
Learn how to fit a linear regression and use your model to score new data. In part 4 of this series, we created our modeling dataset by including a column to identify the rows to be used for training and validating our model. Here, we will create our first model
Learn how to split your data into a training and validation data set to be used for modeling. In part 3 of this series, we replaced the missing values with imputed values. Our final step in preparing the data for modeling is to split the data into a training and
In part 1 of this series, we examined our data before building any models. Among the discoveries were missing values in some of our columns. Missing values are an inevitable part of data analysis. Whether it's due to a faulty sensor, human error, or simply the absence of information, missing
Welcome to the continuation of my series Getting Started with Python Integration to SAS Viya. In this post I'll discuss how to load multiple CSV files into memory as a single table using the loadTable action. Load and prepare data on the CAS server To start, we need to create multiple
Welcome to the continuation of my series Getting Started with Python Integration to SAS Viya. In this post I'll discuss how to update rows in a distributed CAS table. Load and prepare data in the CAS server I created a script to load and prepare data in the CAS server. This
Welcome to the continuation of my series Getting Started with Python Integration to SAS Viya. In this post I'll discuss saving CAS tables to a caslib's data source as a file. This is similar to saving pandas DataFrames using to_ methods. Load and preview the CAS table First, I imported the
In part 1 of this series, we examined our data before building any models. Among the discoveries was a column that seemed to contain a SAS date value. Here, we will discuss what exactly is meant by a 'SAS date', how to format it correctly, and how to create a
Welcome to the continuation of my series Getting Started with Python Integration to SAS Viya. In this post I'll discuss how to execute SQL with the Python SWAT package in the distributed CAS server. Prepare and load data to the CAS server I created a Python function named createDemoData to prepare
Welcome to the continuation of my series Getting Started with Python Integration to SAS Viya. In this post I'll discuss how to count missing values in a CAS table using the Python SWAT package. Load and prepare data First, I connect my Python client to the distributed CAS server and named
Welcome to my series on getting started with Python integration to SAS Viya for predictive modeling. Exploring Data - Learn how to explore the data before fitting a model Working with Dates - Learn how to format a SAS Date and calculate a new column Imputing Missing Values - Learn
Welcome to the first post in my series Getting Started with Python Integration to SAS Viya for Predictive Modeling. I'm going to dive right into the content assuming you have minimal knowledge on SAS Cloud Analytic Services (CAS), CAS Actions and Python. For some background on these subjects, refer to
Welcome to the continuation of my series Getting Started with Python Integration to SAS Viya. In this post I'll discuss how to bring a distributed CAS table back to your Python client as a DataFrame. In this example, I'm using Python on my laptop (Python client) to connect to the
Welcome to the continuation of my series Getting Started with Python Integration to SAS Viya. In previous posts, I discussed how to connect to the CAS server, how to execute CAS actions, and how your data is organized on the CAS server. In this post I'll discuss loading client-side CSV files into
Welcome to the continuation of my series Getting Started with Python Integration to SAS Viya. In previous posts, I discussed how to connect to the CAS server, working with CAS actions and CASResults objects, and how to summarize columns. Now it's time to focus on how to get the count of unique values
Welcome to the continuation of my series Getting Started with Python Integration to SAS Viya. In previous posts, I discussed how to connect to the CAS server, how to execute CAS actions, and how to summarize columns. Now it's time to focus on how to rename columns in CAS tables. Load and explore data
Group and aggregate CAS tables Welcome to the continuation of my series Getting Started with Python Integration to SAS Viya. In previous posts, I discussed how to connect to the CAS server, how to execute CAS actions, and how to summarize columns. Now it's time to focus on how to group and aggregate CAS
Welcome to the continuation of my series Getting Started with Python Integration to SAS Viya. In previous posts, I discussed how to connect to the CAS server, how to execute CAS actions, and how to filter CAS tables. Now it's time to focus on how to summarize columns. Load and explore data Let's first load
Welcome to the continuation of my series Getting Started with Python Integration to SAS Viya. In previous posts, I discussed how to connect to the CAS server, how to execute CAS actions, and how to filter CAS tables. Now it's time to focus on creating calculated columns on a CAS table. Load and explore
Welcome to the seventh installment in my series Getting Started with Python Integration to SAS Viya. In previous posts, I discussed how to connect to the CAS server, how to execute CAS actions, and how to work with the results. Now it's time to learn how to filter CAS tables. Load and explore data
Welcome to the sixth installment in my series Getting Started with Python Integration to SAS Viya. In previous posts, I discussed how to connect to the CAS server, how to execute CAS actions, and how to work with the results. Now it's time to generate simple descriptive statistics of a CAS table. Let's begin
Welcome to the fifth installment in my series Getting Started with Python Integration to SAS Viya. In previous posts, I discussed how to connect to the CAS server, how to execute CAS actions, how to work with the results, and how your data is organized on the CAS server. In
Welcome to the fourth installment in my series Getting Started with Python Integration to SAS Viya. In previous posts, I discussed how to connect to the CAS server, how to execute CAS actions, and how to work with the results. Now it's time to understand how your data is organized
Are you looking for a specific CAS action to use in your project? Maybe you need to create a linear or logistic regression and can't seem to find the CAS action? In this post in the Getting Started with Python Integration to SAS® Viya® series, we are going to look
In the second post of the Getting Started with Python Integration to SAS® Viya® series we will learn about Working with CAS Actions and CASResults Objects. CAS actions are commands sent to the CAS server to run a task, and CASResults objects contain information returned from the CAS server. This
CAS Actions and Action Sets - a brief intro - A quick introduction about the distributed CAS server in SAS® Viya®. Index of articles on Getting Started with Python Integration to SAS Viya. Making a Connection - An introduction to SAS Viya and the massively parallel processing CAS engine, and
