Smarten

MAY 29, 2023

Look for a solution that provides the following capabilities: A Free Trial period during which the organization can test the solution against requirements. The ability to create, share and use unlimited predictive model objects. Automatic generation of models. Automatic generation of models.

Prescriptive Analytics 52

Prescriptive Analytics Predictive Modeling Digital Transformation Business Objectives 52

Smarten

JUNE 29, 2018

This article focuses on the Independent Samples T Test technique of Hypothesis testing. What is the Independent Samples T Test Method of Hypothesis Testing? Let’s look at a sample of the Independent t-test on two variables. One is a dimension containing two values and the other is a measure. About Smarten.

Testing 40

Testing Statistics IT Business Intelligence 40

Cloudera

OCTOBER 14, 2020

Many companies build machine learning models using libraries, whether they are building perception layers for autonomous vehicles, allowing autonomous vehicle operation, or modeling a complex jet engine. Step 1: Using the training data to create a model/classifier. Fig 1: Turbofan jet engine.

Machine Learning 97

Machine Learning Modeling Cost-Benefit Testing 97

DataRobot

MAY 25, 2021

DataRobot is excited to be awarded the 2021 ACT-IAC Innovation Award for ContagionNET, our pioneering rapid antigen test for COVID-19 that is at the forefront of pandemic preparedness and response. As part of these efforts, we built accurate predictive models to determine the spread of the disease weeks and months in advance of a surge.

Testing 52

Testing Predictive Modeling Data-driven Reporting 52

Paul Blogs on BI

MARCH 25, 2020

This first metric requires people to be tested and, as we all know, that is only possible in places where testing is available (and confirmation takes a few days) and only a fraction of people have been tested. As more testing becomes available this first metric will increase significantly. Stay healthy.

Business Intelligence 51

Business Intelligence Measurement Metrics Cost-Benefit 51

Domino Data Lab

OCTOBER 7, 2020

The Curse of Dimensionality , or Large P, Small N, ((P >> N)) , problem applies to the latter case of lots of variables measured on a relatively few number of samples. MANOVA, for example, can test if the heights and weights in boys and girls is different. The accuracy of any predictive model approaches 100%.

Statistics 145

Statistics Testing Predictive Modeling Modeling 145

CIO Business Intelligence

JUNE 7, 2022

Predictive analytics is often considered a type of “advanced analytics,” and frequently depends on machine learning and/or deep learning. Prescriptive analytics is a type of advanced analytics that involves the application of testing and other techniques to recommend specific solutions that will deliver desired outcomes.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

O'Reilly on Data

DECEMBER 12, 2019

Model debugging is an emergent discipline focused on finding and fixing problems in ML systems. In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. Residual analysis is another well-known family of model debugging techniques.

Machine Learning 197

Machine Learning Modeling Testing Risk Management 197

BizAcuity

APRIL 1, 2023

Predictive modeling for flagging suspicious activity Predictive analytics can be used to analyze past customer behavior and transactions to identify patterns that may indicate potential money laundering activity. Building a predictive model is a continuous process and commitment.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

Smart Data Collective

MARCH 28, 2022

It can be further classified as statistical and predictive modeling, but the two are closely associated with each other. Prescriptive data analytics: It is used to predict outcomes and necessary subsequent actions by combining the features of big data and AI. They can be again classified as random testing and optimization.

Data Analytics 82

Data Analytics Software Analytics Statistics 82

CIO Business Intelligence

MAY 26, 2022

Expectedly, advances in artificial intelligence (AI), machine learning (ML), and predictive modeling are giving enterprises – as well as small/medium-sized businesses – a never-before opportunity to automate their recruitment even as they deal with radical changes in workplace practices involving remote and hybrid work.

Advertising 127

Advertising Machine Learning Software Measurement 127

BizAcuity

JANUARY 18, 2023

Predictive modeling for flagging suspicious activity. Predictive analytics can be used to analyze past customer behavior and transactions to identify patterns that may indicate potential money laundering activity. Steps to building a highly accurate predictive model for AML. These include-. REFERENCES. [1]

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

O'Reilly on Data

MAY 18, 2020

All predictive models are wrong at times?—just As the renowned statistician George Box once quipped , “All models are wrong, but some are useful.” Broadly speaking, materiality is the product of the impact of a model error times the probability of that error occuring. just hopefully less so than humans.

Risk 361

Risk Modeling Data Processing Software 361

CIO Business Intelligence

MAY 28, 2022

Expectedly, advances in artificial intelligence (AI), machine learning (ML), and predictive modeling are giving enterprises – as well as small/medium-sized businesses – a never-before opportunity to automate their recruitment even as they deal with radical changes in workplace practices involving remote and hybrid work.

Advertising 118

Advertising Machine Learning Software Measurement 118

IBM Big Data Hub

JUNE 29, 2023

First, availability measures the operational capacity of an asset over time. While reliability and availability are both measured in percentages, it’s possible—even likely—that these percentages will differ even when referring to the same piece of equipment.

Cost-Benefit 84

Cost-Benefit Measurement Management Predictive Analytics 84

DataRobot

NOVEMBER 29, 2021

As with model accuracy, there are many metrics one can use to measure bias. Bias by representation examines if the outcomes predicted by the model vary for protected features. Bias by error examines if the model’s error rates are different for the protected features. Watch webinar with DataCamp on Responsible AI.

Technology 52

Technology Metrics Predictive Modeling Modeling 52

Business Over Broadway

SEPTEMBER 27, 2018

In this paper, I show you how marketers can improve their customer retention efforts by 1) integrating disparate data silos and 2) employing machine learning predictive analytics. Your marketing strategy is only as good as your ability to deliver measurable results. genetic counseling, genetic testing).

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

DataRobot Blog

JUNE 23, 2022

Most successful ML and AI projects are replacing an existing prediction with a more accurate and/or faster one. Human intuition is relied on, or an older, hand-build BI/predictive model exists, or perhaps a set of heuristics were documented that more or less predict something. Automate and Scale Your Decisions.

Predictive Modeling 59

Predictive Modeling Modeling Data Science Measurement 59

DataKitchen

SEPTEMBER 21, 2023

In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets. Running these automated tests as part of your DataOps and Data Observability strategy allows for early detection of discrepancies or errors. What is Data in Use?

Testing 176

Testing Data Quality Predictive Modeling Metrics 176

Smarten

JUNE 29, 2018

Correlation is a statistical measure that indicates the extent to which two variables fluctuate together A positive correlation indicates the extent to which those variables increase or decrease in parallel. The Spearman’s Rank Correlation is a measure of correlation between two ranked (ordered) variables. About Smarten.

Business Analysis 40

Business Analysis IT Measurement Statistics 40

Smarten

JUNE 29, 2018

Correlation is a statistical measure that indicates the extent to which two variables fluctuate together. The Karl Pearson’s correlation measures the degree of linear relationship between two variables. A positive correlation indicates the extent to which those variables increase or decrease in parallel.

Enterprise 40

Enterprise IT Statistics Business Intelligence 40

Smarten

JUNE 29, 2018

Business Problem: An ecommerce company wants to measure the impact of product price, product promotions, and holiday seasonality on product sales. Business Problem: An agriculture production firm wants to predict the impact of the amount of rainfall, humidity, and temperature on the yield of particular crop. Use Case – 1.

Business Analysis 40

Business Analysis IT Sales Statistics 40

Cloudera

FEBRUARY 16, 2022

Will the model correctly determine it is a muffin or get confused and think it is a chihuahua? The extent to which we can predict how the model will classify an image given a change input (e.g. blueberry spacing) is a measure of the model’s interpretability. The complete list is shown below: Model Lineage .

Machine Learning 82

Machine Learning Modeling Metadata Recreation/Entertainment 82

Smarten

JUNE 29, 2018

Business Problem: An eCommerce company wants to measure the impact of product price on product sales. The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.

Enterprise 40

Enterprise Sales Statistics Business Intelligence 40

Birst BI

OCTOBER 30, 2018

The credit scores generated by the predictive model are then used to approve or deny credit cards or loans to customers. A well-designed credit scoring algorithm will properly predict both the low- and high-risk customers. Integrate the data sources of the various behavioral attributes into a functional data model.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

Smarten

JUNE 29, 2018

Logistic regression measures the relationship between the categorical target variable and one or more independent variables. In this article, we will discuss the Binary Logistic Regression Classification method of analysis, and how it can be used in business. What is Binary Logistic Regression Classification?

IT 40

IT Business Intelligence Predictive Modeling Statistics 40

Smarten

JUNE 26, 2018

Logistic regression measures the relationship between the categorical target variable and one or more independent variables It deals with situations in which the outcome for a target variable can have two or more possible types. What is the Multinomial-Logistic Regression Classification Algorithm?

IT 40

IT Business Intelligence Predictive Modeling Statistics 40

Insight

AUGUST 5, 2020

This created a summary features matrix of 7472 recordings x 176 summary features, which was used for training emotion label prediction models. Prediction models An Exploratory Data Analysis showed improved performance was dependent on gender and emotion. up to 20% for prediction of ‘happy’ in females?

Predictive Modeling 98

Predictive Modeling Statistics Modeling Measurement 98

Domino Data Lab

NOVEMBER 17, 2020

High throughput screening technologies have been developed to measure all the molecules of interest in a sample in a single experiment (e.g., Predictive models fit to noise approach 100% accuracy. For example, it’s impossible to know if your predictive model is accurate because it is fitting important variables or noise.

Statistics 131

Statistics Measurement Testing Predictive Modeling 131

DataRobot Blog

JULY 22, 2022

That requires a good model governance framework. At many organizations, the current framework focuses on the validation and testing of new models, but risk managers and regulators are coming to realize that what happens after model deployment is at least as important. Legacy Models. Future Models.

Modeling 105

Modeling Risk Management Testing Risk 105

O'Reilly on Data

SEPTEMBER 15, 2020

Technical sophistication: Sophistication measures a team’s ability to use advanced tools and techniques (e.g., Technical competence: Competence measures a team’s ability to successfully deliver on initiatives and projects. They’re not new to the field; they’ve solved problems, and have discovered what does and doesn’t work.

Cost-Benefit 299

Cost-Benefit Advertising ROI Machine Learning 299

Cloudera

SEPTEMBER 7, 2023

But these measures alone may not be sufficient to protect proprietary information. Even when backed by robust security measures, an external AI service is a tempting, outsized target for potential security breaches: each integration point, data transfer, or externally exposed API becomes a target for malicious actors.

Insurance 79

Insurance Risk Data-driven Modeling 79

CIO Business Intelligence

MARCH 22, 2023

However, there is still a market need for solutions deployed across the ML lifecycle (before and after model training) to protect PII while accessing vast datasets – without drastically changing the methodology and hardware used today. In the training phase, the primary objective is to use existing examples to train a model.

Machine Learning 105

Machine Learning Cost-Benefit Modeling Risk 105

Alation

APRIL 14, 2022

Automatic sampling to test transformation. They strove to ramp up skills in all manner of predictive modeling, machine learning, AI, or even deep learning. AI/ML models pose a problem with versioning results and testing using unique testing and algorithms. A useful feature for exposing patterns in the data.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

CIO Business Intelligence

AUGUST 15, 2023

In partnership with OpenAI and Microsoft, CarMax worked to develop, test, and iterate GPT-3 natural language models aimed at achieving those results. The CarMax team also gathered, scrubbed and formatted data from thousands of vehicles to feed into the models, fine-tuning them as the project advanced.

IT 98

IT Manufacturing IoT Cost-Benefit 98

Smarten

JULY 10, 2018

Independent Samples T Test: What is the Independent Samples T Test Method of Analysis and How Can it Benefit an Organization? Use Case(s): Predict if loan default based on attributes of applicant; predict likelihood of successful treatment of new patient based on patient attributes and more.

Analytics 40

Analytics Forecasting Statistics Sales 40

Domino Data Lab

AUGUST 20, 2019

The problem is that a new unique identifier of a test example won’t be anywhere in the tree. Feature extraction means moving from low-level features that are unsuitable for learning—practically speaking, we get poor testing results—to higher-level features which are useful for learning. Separate out a hold-out test set.

Testing 68

Testing Modeling Interactive Measurement 68