Your English writing platform
Discover LudwigSuggestions(1)
Exact(7)
A decision tree is a logical model represented as a binary (two-way split) tree that shows how the values of a target (dependent) variable can be predicted using the values of a set of predictor (independent) variables.
The former uses a local structure preservation scheme to exploit as much information as possible from the observable data, and the latter is responsible for estimating the missing values of a target gene by considering all of its neighbors rather than a subset of them.
Average threshold cycle (Ct) values of 18S mRNA (chosen as normalizer) were subtracted from the corresponding average Ct values of a target mRNA to obtain ΔCt values.
This target was multivalent, i.e. the target contained one value of each discrimination task (i.e. one out of two colors, one out of two orientations, one out of two sizes and one out of two line types) resulting in 16 possible values of a target.
Successful application requires information to be tailored to the needs and values of a target group [ 30].
In all analyses, the ΔCT values of a target gene were first calculated (i.e., ΔCT[gene] = CT[gene] − CT[18S]).
Similar(53)
The problem is particularly acute in the financial industry, where, these days, the value of a target's assets and liabilities is simply unknown.
Bidders see an opportunity to raise the value of a target by giving its cash to shareholders.
Thus, financial valuation and other methods often operate as complementary platforms that socially construct the value of a target.
In doing so, the perceived value of a target will often depend on which valuation method is used.
Decision tree learning uses a decision tree to create a model that predicts the value of a target variable based on several input variables.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com