Jaida  Kessler

Jaida Kessler


Impute missing values using KNNImputer or IterativeImputer

Need something better than SimpleImputer for missing value imputation?
Try KNNImputer or IterativeImputer (inspired by R’s MICE package). Both are multivariate approaches (they take other features into account!)

#data-science #machine-learning #developer

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Buddha Community

Impute missing values using KNNImputer or IterativeImputer

Why Use WordPress? What Can You Do With WordPress?

Can you use WordPress for anything other than blogging? To your surprise, yes. WordPress is more than just a blogging tool, and it has helped thousands of websites and web applications to thrive. The use of WordPress powers around 40% of online projects, and today in our blog, we would visit some amazing uses of WordPress other than blogging.
What Is The Use Of WordPress?

WordPress is the most popular website platform in the world. It is the first choice of businesses that want to set a feature-rich and dynamic Content Management System. So, if you ask what WordPress is used for, the answer is – everything. It is a super-flexible, feature-rich and secure platform that offers everything to build unique websites and applications. Let’s start knowing them:

1. Multiple Websites Under A Single Installation
WordPress Multisite allows you to develop multiple sites from a single WordPress installation. You can download WordPress and start building websites you want to launch under a single server. Literally speaking, you can handle hundreds of sites from one single dashboard, which now needs applause.
It is a highly efficient platform that allows you to easily run several websites under the same login credentials. One of the best things about WordPress is the themes it has to offer. You can simply download them and plugin for various sites and save space on sites without losing their speed.

2. WordPress Social Network
WordPress can be used for high-end projects such as Social Media Network. If you don’t have the money and patience to hire a coder and invest months in building a feature-rich social media site, go for WordPress. It is one of the most amazing uses of WordPress. Its stunning CMS is unbeatable. And you can build sites as good as Facebook or Reddit etc. It can just make the process a lot easier.
To set up a social media network, you would have to download a WordPress Plugin called BuddyPress. It would allow you to connect a community page with ease and would provide all the necessary features of a community or social media. It has direct messaging, activity stream, user groups, extended profiles, and so much more. You just have to download and configure it.
If BuddyPress doesn’t meet all your needs, don’t give up on your dreams. You can try out WP Symposium or PeepSo. There are also several themes you can use to build a social network.

3. Create A Forum For Your Brand’s Community
Communities are very important for your business. They help you stay in constant connection with your users and consumers. And allow you to turn them into a loyal customer base. Meanwhile, there are many good technologies that can be used for building a community page – the good old WordPress is still the best.
It is the best community development technology. If you want to build your online community, you need to consider all the amazing features you get with WordPress. Plugins such as BB Press is an open-source, template-driven PHP/ MySQL forum software. It is very simple and doesn’t hamper the experience of the website.
Other tools such as wpFoRo and Asgaros Forum are equally good for creating a community blog. They are lightweight tools that are easy to manage and integrate with your WordPress site easily. However, there is only one tiny problem; you need to have some technical knowledge to build a WordPress Community blog page.

4. Shortcodes
Since we gave you a problem in the previous section, we would also give you a perfect solution for it. You might not know to code, but you have shortcodes. Shortcodes help you execute functions without having to code. It is an easy way to build an amazing website, add new features, customize plugins easily. They are short lines of code, and rather than memorizing multiple lines; you can have zero technical knowledge and start building a feature-rich website or application.
There are also plugins like Shortcoder, Shortcodes Ultimate, and the Basics available on WordPress that can be used, and you would not even have to remember the shortcodes.

5. Build Online Stores
If you still think about why to use WordPress, use it to build an online store. You can start selling your goods online and start selling. It is an affordable technology that helps you build a feature-rich eCommerce store with WordPress.
WooCommerce is an extension of WordPress and is one of the most used eCommerce solutions. WooCommerce holds a 28% share of the global market and is one of the best ways to set up an online store. It allows you to build user-friendly and professional online stores and has thousands of free and paid extensions. Moreover as an open-source platform, and you don’t have to pay for the license.
Apart from WooCommerce, there are Easy Digital Downloads, iThemes Exchange, Shopify eCommerce plugin, and so much more available.

6. Security Features
WordPress takes security very seriously. It offers tons of external solutions that help you in safeguarding your WordPress site. While there is no way to ensure 100% security, it provides regular updates with security patches and provides several plugins to help with backups, two-factor authorization, and more.
By choosing hosting providers like WP Engine, you can improve the security of the website. It helps in threat detection, manage patching and updates, and internal security audits for the customers, and so much more.

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#use of wordpress #use wordpress for business website #use wordpress for website #what is use of wordpress #why use wordpress #why use wordpress to build a website

Alec  Nikolaus

Alec Nikolaus


Tutorial On Missingno - Python Tool To Visualize Missing Values

Individuals working in the field of Data Science understand the importance of data. Data is the resource to fuel a machine learning model. But raw data in the real world cannot be used without pre-processing them to a usable format. One of the most common problems faced with real-time data is missing values. There are some values in rows and columns that simply do not exist. But, for a good model training, we need the data to be as clean as possible.

Missing values are generally represented with NaN which stands for Not a Number. Although Pandas library provides methods to impute values to these missing rows and columns, we need to be able to understand how, where and how many points of NaN are distributed in the dataset. For this, python introduced a new library called Missingno.

The purpose of this article is to get a better understanding of missing data by visualizing them using Missingno.

#developers corner #missing value dataset #missing values #missingno #python

Layla  Gerhold

Layla Gerhold


The robustness of Machine Learning algorithms against missing or abnormal values

Let’s explore how classic machine learning algorithms perform when confronted with abnormal data and the benefits provided by standard imputation methods.

#machine-learning #imputation #robustness #algorithms #missing-values

Jaida  Kessler

Jaida Kessler


Impute missing values using KNNImputer or IterativeImputer

Need something better than SimpleImputer for missing value imputation?
Try KNNImputer or IterativeImputer (inspired by R’s MICE package). Both are multivariate approaches (they take other features into account!)

#data-science #machine-learning #developer

Tyshawn  Braun

Tyshawn Braun


Missing Value Imputation – A Review

Missing values occur in all kinds of datasets from industry to academia. They can be represented differently - sometimes by a question mark, or -999, sometimes by “n/a”, or by some other dedicated number or character. Detecting and handling missing values in the correct way is important, as they can impact the results of the analysis, and there are algorithms that can’t handle them. So what is the correct way?

How to choose the correct strategy

Two common approaches to imputing missing values is to replace all missing values with either a fixed value, for example zero, or with the mean of all available values. Which approach is better?

Let’s see the effects on two different case studies:

  • Case Study 1: threshold-based anomaly detection on sensor data
  • Case Study 2: a report of customer aggregated data

Case Study 1: Imputation for threshold-based anomaly detection

In a classic threshold-based solution for anomaly detection, a threshold, calculated from the mean and variance of the original data, is applied to the sensor data to generate an alarm. If the missing values are imputed with a fixed value, e.g. zero, this will affect the calculation of the mean and variance used for the threshold definition. This would likely lead to a wrong estimate of the alarm threshold and to some expensive downtime.

Here imputing the missing values with the mean of the available values is the right way to go.

Case Study 2: Imputation for aggregated customer data

In a classic reporting exercise on customer data, the number of customers and the total revenue for each geographical area of the business needs to be aggregated and visualized, for example via bar charts. The customer dataset has missing values for those areas where the business has not started or has not picked up and no customers and no business have been recorded yet. In this case, using the mean value of the available numbers to impute the missing values would make up customers and revenues where neither customers nor revenues are present.

**The right way to go here is to impute the missing values with a fixed value of zero. **

In both cases, it is our knowledge of the process that suggests to us the right way to proceed in imputing missing values. In the case of sensor data, missing values are due to a malfunctioning of the measuring machine and therefore real numerical values are just not recorded. In the case of the customer dataset, missing values appear where there is nothing to measure yet.

You see already from these two examples, that there is no panacea for all missing value imputation problems and clearly we can’t provide an answer to the classic question: “which strategy is correct for missing value imputation for my dataset?” The answer is too dependent on the domain and the business knowledge.

We can however provide a review of the most commonly used techniques to:

  • Detect whether the dataset contains missing values and of which type,
  • Impute the missing values.

#overviews #data preprocessing #knime #machine learning #missing values