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Комбинируя алгоритмы работы

машинного обучения с большими

объемами данных и лучшие практики

планирования, Brain2Logic позволяет создать в Anaplan гибкое

решение для комплексных бизнес-

процессов.

Подход к планированию

Организация

непрерывного процесса

планирования

Экспертиза

Поиск компромиссных

вариантов и принятие

ключевых решений

Brain2Logic

Предиктивная аналитика

и алгоритмы

машинного обучения

Какие задачи решаем

Image by Georgie Cobbs
  • Прогноз продаж текущей продуктовой линейки;

  • Прогноз продаж новых продуктов     и продуктов с коротким жизненным циклом;

  • Прогноз продаж по продуктам, зависимых от внешних факторов;

  • Планирование промо активностей;

  • Кластеризация клиентов ипродуктов

  • Поведение клиентов (отток/приток).

Какие методы использует Brain2Logic

HOLT WINTER’S 

EXPONENTIAL SMOOTHING

Holt Winter's Exponential Smoothing (HWES) is a triple exponential smoothing model, also known as the Holt-Winters method, which allows you to take into account the trend and seasonality of the time series.

XGBOOST

XGBoost is a gradient boosting algorithm for decision trees. Gradient boosting is a machine learning technique for classification and regression problems that builds a prediction model in the form of an ensemble of weak predictive models, usually decision trees. The model is new and very promising.

FACEBOOK PROPHET

The Prophet library is a model developed by Facebook to predict time series data based on an additive model in which non-linear trends are consistent with annual, weekly and daily seasonality, as well as holiday effects.

LONG SHORT-TERM MEMORY 

Long short-term memory (LSTM) is an artificial recurrent architecture

neural network (RNN) used in the field of deep learning. Models of this class, inspired by the structure of the human brain, are complex and require more time and resource-intensive training, but at the same time make complex forecasts depending on many third-party factors.

SARIMAX

SARIMAX (Seasonal AutoRegressive Integrated Moving Average with eXogenous regressors model) is the Box-Jenkins model,

integrated autoregressive model

and moving average. Fixes a set of different time structures

in data, for example, reveals a trend, seasonality, influence

third-party factors.

Принцип работы

SARIMAX (Seasonal AutoRegressive Integrated Moving Average with eXogenous regressors model) is the Box-Jenkins model,

integrated autoregressive model

and moving average. Fixes a set of different time structures

in data, for example, reveals a trend, seasonality, influence

third-party factors.

Ваши наборы данных

Автоматический подбор моделей

SARIMAX (Seasonal AutoRegressive Integrated Moving Average with eXogenous regressors model) is the Box-Jenkins model,

integrated autoregressive model

and moving average. Fixes a set of different time structures

in data, for example, reveals a trend, seasonality, influence

third-party factors.

Управление и кастомизация

SARIMAX (Seasonal AutoRegressive Integrated Moving Average with eXogenous regressors model) is the Box-Jenkins model,

integrated autoregressive model

and moving average. Fixes a set of different time structures

in data, for example, reveals a trend, seasonality, influence

third-party factors.

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